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[FreeCourseSite.com] Udemy - The Data Science Course 2021 Complete Data Science Bootcamp
magnet:?xt=urn:btih:b11e7c94dd27ce69edfe823853cdabbb168ff721&dn=[FreeCourseSite.com] Udemy - The Data Science Course 2021 Complete Data Science Bootcamp
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b11e7c94dd27ce69edfe823853cdabbb168ff721
点击数:
106
文件大小:
15.23 GB
文件数量:
386
创建日期:
2021-12-14 14:23
最后访问:
2024-7-17 21:05
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FreeCourseSite
com
Udemy
-
The
Data
Science
Course
2021
Complete
Data
Science
Bootcamp
文件列表详情
1. Part 1 Introduction/1. A Practical Example What You Will Learn in This Course.mp4 49.04 MB
1. Part 1 Introduction/2. What Does the Course Cover.mp4 62.25 MB
10. Probability - Combinatorics/1. Fundamentals of Combinatorics.mp4 16.21 MB
10. Probability - Combinatorics/11. Solving Combinations.mp4 57.34 MB
10. Probability - Combinatorics/13. Symmetry of Combinations.mp4 40.3 MB
10. Probability - Combinatorics/15. Solving Combinations with Separate Sample Spaces.mp4 33.15 MB
10. Probability - Combinatorics/17. Combinatorics in Real-Life The Lottery.mp4 41.29 MB
10. Probability - Combinatorics/19. A Recap of Combinatorics.mp4 38.49 MB
10. Probability - Combinatorics/20. A Practical Example of Combinatorics.mp4 134.31 MB
10. Probability - Combinatorics/3. Permutations and How to Use Them.mp4 42.72 MB
10. Probability - Combinatorics/5. Simple Operations with Factorials.mp4 36.11 MB
10. Probability - Combinatorics/7. Solving Variations with Repetition.mp4 34 MB
10. Probability - Combinatorics/9. Solving Variations without Repetition.mp4 43.14 MB
11. Probability - Bayesian Inference/1. Sets and Events.mp4 53.46 MB
11. Probability - Bayesian Inference/11. Dependence and Independence of Sets.mp4 34.78 MB
11. Probability - Bayesian Inference/13. The Conditional Probability Formula.mp4 45.86 MB
11. Probability - Bayesian Inference/15. The Law of Total Probability.mp4 34.93 MB
11. Probability - Bayesian Inference/16. The Additive Rule.mp4 26.97 MB
11. Probability - Bayesian Inference/18. The Multiplication Law.mp4 49.02 MB
11. Probability - Bayesian Inference/20. Bayes' Law.mp4 49.93 MB
11. Probability - Bayesian Inference/22. A Practical Example of Bayesian Inference.mp4 145.13 MB
11. Probability - Bayesian Inference/3. Ways Sets Can Interact.mp4 47.43 MB
11. Probability - Bayesian Inference/5. Intersection of Sets.mp4 26.96 MB
11. Probability - Bayesian Inference/7. Union of Sets.mp4 57.19 MB
11. Probability - Bayesian Inference/9. Mutually Exclusive Sets.mp4 25.4 MB
12. Probability - Distributions/1. Fundamentals of Probability Distributions.mp4 73.4 MB
12. Probability - Distributions/11. Discrete Distributions The Binomial Distribution.mp4 68.83 MB
12. Probability - Distributions/13. Discrete Distributions The Poisson Distribution.mp4 55.76 MB
12. Probability - Distributions/15. Characteristics of Continuous Distributions.mp4 84.12 MB
12. Probability - Distributions/17. Continuous Distributions The Normal Distribution.mp4 48.24 MB
12. Probability - Distributions/19. Continuous Distributions The Standard Normal Distribution.mp4 47.9 MB
12. Probability - Distributions/21. Continuous Distributions The Students' T Distribution.mp4 27.18 MB
12. Probability - Distributions/23. Continuous Distributions The Chi-Squared Distribution.mp4 26.34 MB
12. Probability - Distributions/25. Continuous Distributions The Exponential Distribution.mp4 40.23 MB
12. Probability - Distributions/27. Continuous Distributions The Logistic Distribution.mp4 47.05 MB
12. Probability - Distributions/29. A Practical Example of Probability Distributions.mp4 157.83 MB
12. Probability - Distributions/3. Types of Probability Distributions.mp4 71.07 MB
12. Probability - Distributions/5. Characteristics of Discrete Distributions.mp4 22.7 MB
12. Probability - Distributions/7. Discrete Distributions The Uniform Distribution.mp4 24.39 MB
12. Probability - Distributions/9. Discrete Distributions The Bernoulli Distribution.mp4 34.14 MB
13. Probability - Probability in Other Fields/1. Probability in Finance.mp4 99.06 MB
13. Probability - Probability in Other Fields/2. Probability in Statistics.mp4 77.28 MB
13. Probability - Probability in Other Fields/3. Probability in Data Science.mp4 63.49 MB
14. Part 3 Statistics/1. Population and Sample.mp4 58.11 MB
15. Statistics - Descriptive Statistics/1. Types of Data.mp4 72.53 MB
15. Statistics - Descriptive Statistics/11. The Histogram.mp4 13.78 MB
15. Statistics - Descriptive Statistics/14. Cross Tables and Scatter Plots.mp4 39.81 MB
15. Statistics - Descriptive Statistics/17. Mean, median and mode.mp4 37.12 MB
15. Statistics - Descriptive Statistics/19. Skewness.mp4 19.4 MB
15. Statistics - Descriptive Statistics/22. Variance.mp4 50.95 MB
15. Statistics - Descriptive Statistics/24. Standard Deviation and Coefficient of Variation.mp4 45.12 MB
15. Statistics - Descriptive Statistics/27. Covariance.mp4 27.49 MB
15. Statistics - Descriptive Statistics/3. Levels of Measurement.mp4 54.38 MB
15. Statistics - Descriptive Statistics/30. Correlation Coefficient.mp4 29.38 MB
15. Statistics - Descriptive Statistics/5. Categorical Variables - Visualization Techniques.mp4 36.64 MB
15. Statistics - Descriptive Statistics/8. Numerical Variables - Frequency Distribution Table.mp4 25.85 MB
16. Statistics - Practical Example Descriptive Statistics/1. Practical Example Descriptive Statistics.mp4 160.46 MB
17. Statistics - Inferential Statistics Fundamentals/1. Introduction.mp4 15.5 MB
17. Statistics - Inferential Statistics Fundamentals/11. Standard error.mp4 22.77 MB
17. Statistics - Inferential Statistics Fundamentals/13. Estimators and Estimates.mp4 47.83 MB
17. Statistics - Inferential Statistics Fundamentals/2. What is a Distribution.mp4 61.6 MB
17. Statistics - Inferential Statistics Fundamentals/4. The Normal Distribution.mp4 49.85 MB
17. Statistics - Inferential Statistics Fundamentals/6. The Standard Normal Distribution.mp4 22.5 MB
17. Statistics - Inferential Statistics Fundamentals/9. Central Limit Theorem.mp4 62.89 MB
18. Statistics - Inferential Statistics Confidence Intervals/1. What are Confidence Intervals.mp4 49.99 MB
18. Statistics - Inferential Statistics Confidence Intervals/10. Margin of Error.mp4 47.23 MB
18. Statistics - Inferential Statistics Confidence Intervals/12. Confidence intervals. Two means. Dependent samples.mp4 70.47 MB
18. Statistics - Inferential Statistics Confidence Intervals/14. Confidence intervals. Two means. Independent Samples (Part 1).mp4 28.76 MB
18. Statistics - Inferential Statistics Confidence Intervals/16. Confidence intervals. Two means. Independent Samples (Part 2).mp4 26.82 MB
18. Statistics - Inferential Statistics Confidence Intervals/18. Confidence intervals. Two means. Independent Samples (Part 3).mp4 19.93 MB
18. Statistics - Inferential Statistics Confidence Intervals/3. Confidence Intervals; Population Variance Known; Z-score.mp4 78.2 MB
18. Statistics - Inferential Statistics Confidence Intervals/5. Confidence Interval Clarifications.mp4 57.03 MB
18. Statistics - Inferential Statistics Confidence Intervals/6. Student's T Distribution.mp4 35.43 MB
18. Statistics - Inferential Statistics Confidence Intervals/8. Confidence Intervals; Population Variance Unknown; T-score.mp4 32.21 MB
19. Statistics - Practical Example Inferential Statistics/1. Practical Example Inferential Statistics.mp4 102.66 MB
2. The Field of Data Science - The Various Data Science Disciplines/1. Data Science and Business Buzzwords Why are there so Many.mp4 81.41 MB
2. The Field of Data Science - The Various Data Science Disciplines/3. What is the difference between Analysis and Analytics.mp4 53.55 MB
2. The Field of Data Science - The Various Data Science Disciplines/5. Business Analytics, Data Analytics, and Data Science An Introduction.mp4 64.51 MB
2. The Field of Data Science - The Various Data Science Disciplines/7. Continuing with BI, ML, and AI.mp4 108.98 MB
2. The Field of Data Science - The Various Data Science Disciplines/9. A Breakdown of our Data Science Infographic.mp4 67.74 MB
20. Statistics - Hypothesis Testing/1. Null vs Alternative Hypothesis.mp4 92.04 MB
20. Statistics - Hypothesis Testing/10. p-value.mp4 55.87 MB
20. Statistics - Hypothesis Testing/12. Test for the Mean. Population Variance Unknown.mp4 40.24 MB
20. Statistics - Hypothesis Testing/14. Test for the Mean. Dependent Samples.mp4 50.38 MB
20. Statistics - Hypothesis Testing/16. Test for the mean. Independent Samples (Part 1).mp4 33.94 MB
20. Statistics - Hypothesis Testing/18. Test for the mean. Independent Samples (Part 2).mp4 36.39 MB
20. Statistics - Hypothesis Testing/4. Rejection Region and Significance Level.mp4 82.61 MB
20. Statistics - Hypothesis Testing/6. Type I Error and Type II Error.mp4 43.94 MB
20. Statistics - Hypothesis Testing/8. Test for the Mean. Population Variance Known.mp4 54.22 MB
21. Statistics - Practical Example Hypothesis Testing/1. Practical Example Hypothesis Testing.mp4 69.48 MB
22. Part 4 Introduction to Python/1. Introduction to Programming.mp4 58.54 MB
22. Part 4 Introduction to Python/3. Why Python.mp4 75.07 MB
22. Part 4 Introduction to Python/5. Why Jupyter.mp4 44.32 MB
22. Part 4 Introduction to Python/7. Installing Python and Jupyter.mp4 50.99 MB
22. Part 4 Introduction to Python/8. Understanding Jupyter's Interface - the Notebook Dashboard.mp4 13.79 MB
22. Part 4 Introduction to Python/9. Prerequisites for Coding in the Jupyter Notebooks.mp4 30.58 MB
23. Python - Variables and Data Types/1. Variables.mp4 14.08 MB
23. Python - Variables and Data Types/3. Numbers and Boolean Values in Python.mp4 17.06 MB
23. Python - Variables and Data Types/5. Python Strings.mp4 24.15 MB
24. Python - Basic Python Syntax/1. Using Arithmetic Operators in Python.mp4 18.92 MB
24. Python - Basic Python Syntax/10. Indexing Elements.mp4 5.93 MB
24. Python - Basic Python Syntax/12. Structuring with Indentation.mp4 5.47 MB
24. Python - Basic Python Syntax/3. The Double Equality Sign.mp4 5.99 MB
24. Python - Basic Python Syntax/5. How to Reassign Values.mp4 4 MB
24. Python - Basic Python Syntax/7. Add Comments.mp4 4.68 MB
24. Python - Basic Python Syntax/9. Understanding Line Continuation.mp4 2.35 MB
25. Python - Other Python Operators/1. Comparison Operators.mp4 10.17 MB
25. Python - Other Python Operators/3. Logical and Identity Operators.mp4 30.05 MB
26. Python - Conditional Statements/1. The IF Statement.mp4 10.81 MB
26. Python - Conditional Statements/3. The ELSE Statement.mp4 10.84 MB
26. Python - Conditional Statements/4. The ELIF Statement.mp4 25.07 MB
26. Python - Conditional Statements/5. A Note on Boolean Values.mp4 8.9 MB
27. Python - Python Functions/1. Defining a Function in Python.mp4 6.3 MB
27. Python - Python Functions/2. How to Create a Function with a Parameter.mp4 18.08 MB
27. Python - Python Functions/3. Defining a Function in Python - Part II.mp4 11.14 MB
27. Python - Python Functions/4. How to Use a Function within a Function.mp4 8.13 MB
27. Python - Python Functions/5. Conditional Statements and Functions.mp4 15.69 MB
27. Python - Python Functions/6. Functions Containing a Few Arguments.mp4 6.01 MB
27. Python - Python Functions/7. Built-in Functions in Python.mp4 22.01 MB
28. Python - Sequences/1. Lists.mp4 37.8 MB
28. Python - Sequences/3. Using Methods.mp4 37.6 MB
28. Python - Sequences/5. List Slicing.mp4 30.77 MB
28. Python - Sequences/6. Tuples.mp4 29.49 MB
28. Python - Sequences/7. Dictionaries.mp4 41.68 MB
29. Python - Iterations/1. For Loops.mp4 23.59 MB
29. Python - Iterations/3. While Loops and Incrementing.mp4 28.44 MB
29. Python - Iterations/4. Lists with the range() Function.mp4 25.79 MB
29. Python - Iterations/6. Conditional Statements and Loops.mp4 27.76 MB
29. Python - Iterations/7. Conditional Statements, Functions, and Loops.mp4 9.48 MB
29. Python - Iterations/8. How to Iterate over Dictionaries.mp4 29.65 MB
3. The Field of Data Science - Connecting the Data Science Disciplines/1. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4 126.88 MB
30. Python - Advanced Python Tools/1. Object Oriented Programming.mp4 33.59 MB
30. Python - Advanced Python Tools/3. Modules and Packages.mp4 8.5 MB
30. Python - Advanced Python Tools/5. What is the Standard Library.mp4 18.03 MB
30. Python - Advanced Python Tools/7. Importing Modules in Python.mp4 19.94 MB
31. Part 5 Advanced Statistical Methods in Python/1. Introduction to Regression Analysis.mp4 17.33 MB
32. Advanced Statistical Methods - Linear Regression with StatsModels/1. The Linear Regression Model.mp4 57.37 MB
32. Advanced Statistical Methods - Linear Regression with StatsModels/10. Using Seaborn for Graphs.mp4 12.24 MB
32. Advanced Statistical Methods - Linear Regression with StatsModels/11. How to Interpret the Regression Table.mp4 44.64 MB
32. Advanced Statistical Methods - Linear Regression with StatsModels/13. Decomposition of Variability.mp4 49.66 MB
32. Advanced Statistical Methods - Linear Regression with StatsModels/15. What is the OLS.mp4 28.31 MB
32. Advanced Statistical Methods - Linear Regression with StatsModels/17. R-Squared.mp4 41.03 MB
32. Advanced Statistical Methods - Linear Regression with StatsModels/3. Correlation vs Regression.mp4 14.74 MB
32. Advanced Statistical Methods - Linear Regression with StatsModels/5. Geometrical Representation of the Linear Regression Model.mp4 5.12 MB
32. Advanced Statistical Methods - Linear Regression with StatsModels/7. Python Packages Installation.mp4 40.59 MB
32. Advanced Statistical Methods - Linear Regression with StatsModels/8. First Regression in Python.mp4 44.56 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/1. Multiple Linear Regression.mp4 21.52 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/11. A2 No Endogeneity.mp4 35.67 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/13. A3 Normality and Homoscedasticity.mp4 42.7 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/14. A4 No Autocorrelation.mp4 31.51 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/16. A5 No Multicollinearity.mp4 28.7 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/18. Dealing with Categorical Data - Dummy Variables.mp4 55.66 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/20. Making Predictions with the Linear Regression.mp4 24.7 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/3. Adjusted R-Squared.mp4 54.83 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/6. Test for Significance of the Model (F-Test).mp4 16.42 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/7. OLS Assumptions.mp4 21.85 MB
33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/9. A1 Linearity.mp4 12.6 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/1. What is sklearn and How is it Different from Other Packages.mp4 27.25 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/10. Feature Selection (F-regression).mp4 29.51 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/12. Creating a Summary Table with P-values.mp4 12.3 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/14. Feature Scaling (Standardization).mp4 39.08 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/15. Feature Selection through Standardization of Weights.mp4 34.89 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/16. Predicting with the Standardized Coefficients.mp4 25.96 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/18. Underfitting and Overfitting.mp4 16.95 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/19. Train - Test Split Explained.mp4 49.18 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/2. How are we Going to Approach this Section.mp4 19.41 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/3. Simple Linear Regression with sklearn.mp4 34.77 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/4. Simple Linear Regression with sklearn - A StatsModels-like Summary Table.mp4 32 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/7. Multiple Linear Regression with sklearn.mp4 20.07 MB
34. Advanced Statistical Methods - Linear Regression with sklearn/8. Calculating the Adjusted R-Squared in sklearn.mp4 30.88 MB
35. Advanced Statistical Methods - Practical Example Linear Regression/1. Practical Example Linear Regression (Part 1).mp4 97.08 MB
35. Advanced Statistical Methods - Practical Example Linear Regression/2. Practical Example Linear Regression (Part 2).mp4 46 MB
35. Advanced Statistical Methods - Practical Example Linear Regression/4. Practical Example Linear Regression (Part 3).mp4 23.69 MB
35. Advanced Statistical Methods - Practical Example Linear Regression/6. Practical Example Linear Regression (Part 4).mp4 56.04 MB
35. Advanced Statistical Methods - Practical Example Linear Regression/8. Practical Example Linear Regression (Part 5).mp4 57.89 MB
36. Advanced Statistical Methods - Logistic Regression/1. Introduction to Logistic Regression.mp4 27.06 MB
36. Advanced Statistical Methods - Logistic Regression/10. Binary Predictors in a Logistic Regression.mp4 38.43 MB
36. Advanced Statistical Methods - Logistic Regression/12. Calculating the Accuracy of the Model.mp4 32.85 MB
36. Advanced Statistical Methods - Logistic Regression/14. Underfitting and Overfitting.mp4 22.29 MB
36. Advanced Statistical Methods - Logistic Regression/15. Testing the Model.mp4 32.27 MB
36. Advanced Statistical Methods - Logistic Regression/2. A Simple Example in Python.mp4 34.7 MB
36. Advanced Statistical Methods - Logistic Regression/3. Logistic vs Logit Function.mp4 86.49 MB
36. Advanced Statistical Methods - Logistic Regression/4. Building a Logistic Regression.mp4 17.11 MB
36. Advanced Statistical Methods - Logistic Regression/6. An Invaluable Coding Tip.mp4 23.05 MB
36. Advanced Statistical Methods - Logistic Regression/7. Understanding Logistic Regression Tables.mp4 30.55 MB
36. Advanced Statistical Methods - Logistic Regression/9. What do the Odds Actually Mean.mp4 32.28 MB
37. Advanced Statistical Methods - Cluster Analysis/1. Introduction to Cluster Analysis.mp4 53.42 MB
37. Advanced Statistical Methods - Cluster Analysis/2. Some Examples of Clusters.mp4 71.53 MB
37. Advanced Statistical Methods - Cluster Analysis/3. Difference between Classification and Clustering.mp4 36.15 MB
37. Advanced Statistical Methods - Cluster Analysis/4. Math Prerequisites.mp4 14.55 MB
38. Advanced Statistical Methods - K-Means Clustering/1. K-Means Clustering.mp4 27.29 MB
38. Advanced Statistical Methods - K-Means Clustering/10. Relationship between Clustering and Regression.mp4 9.93 MB
38. Advanced Statistical Methods - K-Means Clustering/11. Market Segmentation with Cluster Analysis (Part 1).mp4 43.02 MB
38. Advanced Statistical Methods - K-Means Clustering/12. Market Segmentation with Cluster Analysis (Part 2).mp4 56.11 MB
38. Advanced Statistical Methods - K-Means Clustering/13. How is Clustering Useful.mp4 74.45 MB
38. Advanced Statistical Methods - K-Means Clustering/2. A Simple Example of Clustering.mp4 51.83 MB
38. Advanced Statistical Methods - K-Means Clustering/4. Clustering Categorical Data.mp4 21.24 MB
38. Advanced Statistical Methods - K-Means Clustering/6. How to Choose the Number of Clusters.mp4 44.13 MB
38. Advanced Statistical Methods - K-Means Clustering/8. Pros and Cons of K-Means Clustering.mp4 37.7 MB
38. Advanced Statistical Methods - K-Means Clustering/9. To Standardize or not to Standardize.mp4 30.1 MB
39. Advanced Statistical Methods - Other Types of Clustering/1. Types of Clustering.mp4 44.57 MB
39. Advanced Statistical Methods - Other Types of Clustering/2. Dendrogram.mp4 29.06 MB
39. Advanced Statistical Methods - Other Types of Clustering/3. Heatmaps.mp4 29.62 MB
4. The Field of Data Science - The Benefits of Each Discipline/1. The Reason Behind These Disciplines.mp4 81.18 MB
40. Part 6 Mathematics/1. What is a Matrix.mp4 33.59 MB
40. Part 6 Mathematics/10. Addition and Subtraction of Matrices.mp4 32.61 MB
40. Part 6 Mathematics/12. Errors when Adding Matrices.mp4 11.17 MB
40. Part 6 Mathematics/13. Transpose of a Matrix.mp4 38.08 MB
40. Part 6 Mathematics/14. Dot Product.mp4 23.99 MB
40. Part 6 Mathematics/15. Dot Product of Matrices.mp4 49.43 MB
40. Part 6 Mathematics/16. Why is Linear Algebra Useful.mp4 144.33 MB
40. Part 6 Mathematics/3. Scalars and Vectors.mp4 33.85 MB
40. Part 6 Mathematics/5. Linear Algebra and Geometry.mp4 49.79 MB
40. Part 6 Mathematics/7. Arrays in Python - A Convenient Way To Represent Matrices.mp4 26.67 MB
40. Part 6 Mathematics/8. What is a Tensor.mp4 22.52 MB
41. Part 7 Deep Learning/1. What to Expect from this Part.mp4 31.1 MB
42. Deep Learning - Introduction to Neural Networks/1. Introduction to Neural Networks.mp4 42.93 MB
42. Deep Learning - Introduction to Neural Networks/11. The Linear model with Multiple Inputs and Multiple Outputs.mp4 38.32 MB
42. Deep Learning - Introduction to Neural Networks/13. Graphical Representation of Simple Neural Networks.mp4 22.64 MB
42. Deep Learning - Introduction to Neural Networks/15. What is the Objective Function.mp4 17.91 MB
42. Deep Learning - Introduction to Neural Networks/17. Common Objective Functions L2-norm Loss.mp4 23.27 MB
42. Deep Learning - Introduction to Neural Networks/19. Common Objective Functions Cross-Entropy Loss.mp4 37.24 MB
42. Deep Learning - Introduction to Neural Networks/21. Optimization Algorithm 1-Parameter Gradient Descent.mp4 55.62 MB
42. Deep Learning - Introduction to Neural Networks/23. Optimization Algorithm n-Parameter Gradient Descent.mp4 39.42 MB
42. Deep Learning - Introduction to Neural Networks/3. Training the Model.mp4 28.71 MB
42. Deep Learning - Introduction to Neural Networks/5. Types of Machine Learning.mp4 45.1 MB
42. Deep Learning - Introduction to Neural Networks/7. The Linear Model (Linear Algebraic Version).mp4 28.44 MB
42. Deep Learning - Introduction to Neural Networks/9. The Linear Model with Multiple Inputs.mp4 25.11 MB
43. Deep Learning - How to Build a Neural Network from Scratch with NumPy/1. Basic NN Example (Part 1).mp4 20.59 MB
43. Deep Learning - How to Build a Neural Network from Scratch with NumPy/2. Basic NN Example (Part 2).mp4 34.94 MB
43. Deep Learning - How to Build a Neural Network from Scratch with NumPy/3. Basic NN Example (Part 3).mp4 24.4 MB
43. Deep Learning - How to Build a Neural Network from Scratch with NumPy/4. Basic NN Example (Part 4).mp4 61.14 MB
44. Deep Learning - TensorFlow 2.0 Introduction/1. How to Install TensorFlow 2.0.mp4 38.76 MB
44. Deep Learning - TensorFlow 2.0 Introduction/2. TensorFlow Outline and Comparison with Other Libraries.mp4 33.51 MB
44. Deep Learning - TensorFlow 2.0 Introduction/3. TensorFlow 1 vs TensorFlow 2.mp4 21.99 MB
44. Deep Learning - TensorFlow 2.0 Introduction/4. A Note on TensorFlow 2 Syntax.mp4 6.76 MB
44. Deep Learning - TensorFlow 2.0 Introduction/5. Types of File Formats Supporting TensorFlow.mp4 16.4 MB
44. Deep Learning - TensorFlow 2.0 Introduction/6. Outlining the Model with TensorFlow 2.mp4 34.69 MB
44. Deep Learning - TensorFlow 2.0 Introduction/7. Interpreting the Result and Extracting the Weights and Bias.mp4 30.27 MB
44. Deep Learning - TensorFlow 2.0 Introduction/8. Customizing a TensorFlow 2 Model.mp4 22.91 MB
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/1. What is a Layer.mp4 12.5 MB
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/2. What is a Deep Net.mp4 29.53 MB
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/3. Digging into a Deep Net.mp4 59.36 MB
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/4. Non-Linearities and their Purpose.mp4 27.68 MB
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/5. Activation Functions.mp4 25.09 MB
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/6. Activation Functions Softmax Activation.mp4 25.92 MB
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/7. Backpropagation.mp4 34.95 MB
45. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/8. Backpropagation Picture.mp4 19.51 MB
46. Deep Learning - Overfitting/1. What is Overfitting.mp4 31.08 MB
46. Deep Learning - Overfitting/2. Underfitting and Overfitting for Classification.mp4 25.07 MB
46. Deep Learning - Overfitting/3. What is Validation.mp4 32.71 MB
46. Deep Learning - Overfitting/4. Training, Validation, and Test Datasets.mp4 25.19 MB
46. Deep Learning - Overfitting/5. N-Fold Cross Validation.mp4 20.7 MB
46. Deep Learning - Overfitting/6. Early Stopping or When to Stop Training.mp4 24.17 MB
47. Deep Learning - Initialization/1. What is Initialization.mp4 21.76 MB
47. Deep Learning - Initialization/2. Types of Simple Initializations.mp4 14.31 MB
47. Deep Learning - Initialization/3. State-of-the-Art Method - (Xavier) Glorot Initialization.mp4 17.14 MB
48. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules/1. Stochastic Gradient Descent.mp4 28.68 MB
48. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules/2. Problems with Gradient Descent.mp4 11.01 MB
48. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules/3. Momentum.mp4 16.43 MB
48. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules/4. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.mp4 29.08 MB
48. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules/5. Learning Rate Schedules Visualized.mp4 9.11 MB
48. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules/6. Adaptive Learning Rate Schedules (AdaGrad and RMSprop ).mp4 26.35 MB
48. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules/7. Adam (Adaptive Moment Estimation).mp4 22.35 MB
49. Deep Learning - Preprocessing/1. Preprocessing Introduction.mp4 27.78 MB
49. Deep Learning - Preprocessing/2. Types of Basic Preprocessing.mp4 11.85 MB
49. Deep Learning - Preprocessing/3. Standardization.mp4 50.98 MB
49. Deep Learning - Preprocessing/4. Preprocessing Categorical Data.mp4 18.6 MB
49. Deep Learning - Preprocessing/5. Binary and One-Hot Encoding.mp4 28.95 MB
5. The Field of Data Science - Popular Data Science Techniques/1. Techniques for Working with Traditional Data.mp4 138.3 MB
5. The Field of Data Science - Popular Data Science Techniques/10. Techniques for Working with Traditional Methods.mp4 111.65 MB
5. The Field of Data Science - Popular Data Science Techniques/12. Real Life Examples of Traditional Methods.mp4 42.79 MB
5. The Field of Data Science - Popular Data Science Techniques/13. Machine Learning (ML) Techniques.mp4 99.33 MB
5. The Field of Data Science - Popular Data Science Techniques/15. Types of Machine Learning.mp4 125.14 MB
5. The Field of Data Science - Popular Data Science Techniques/17. Real Life Examples of Machine Learning (ML).mp4 36.82 MB
5. The Field of Data Science - Popular Data Science Techniques/3. Real Life Examples of Traditional Data.mp4 29.93 MB
5. The Field of Data Science - Popular Data Science Techniques/4. Techniques for Working with Big Data.mp4 75.5 MB
5. The Field of Data Science - Popular Data Science Techniques/6. Real Life Examples of Big Data.mp4 22.03 MB
5. The Field of Data Science - Popular Data Science Techniques/7. Business Intelligence (BI) Techniques.mp4 89.94 MB
5. The Field of Data Science - Popular Data Science Techniques/9. Real Life Examples of Business Intelligence (BI).mp4 29.54 MB
50. Deep Learning - Classifying on the MNIST Dataset/1. MNIST The Dataset.mp4 13.38 MB
50. Deep Learning - Classifying on the MNIST Dataset/10. MNIST Learning.mp4 40.96 MB
50. Deep Learning - Classifying on the MNIST Dataset/12. MNIST Testing the Model.mp4 29.53 MB
50. Deep Learning - Classifying on the MNIST Dataset/2. MNIST How to Tackle the MNIST.mp4 18.66 MB
50. Deep Learning - Classifying on the MNIST Dataset/3. MNIST Importing the Relevant Packages and Loading the Data.mp4 16.33 MB
50. Deep Learning - Classifying on the MNIST Dataset/4. MNIST Preprocess the Data - Create a Validation Set and Scale It.mp4 29.04 MB
50. Deep Learning - Classifying on the MNIST Dataset/6. MNIST Preprocess the Data - Shuffle and Batch.mp4 41.52 MB
50. Deep Learning - Classifying on the MNIST Dataset/8. MNIST Outline the Model.mp4 28.24 MB
50. Deep Learning - Classifying on the MNIST Dataset/9. MNIST Select the Loss and the Optimizer.mp4 13.9 MB
51. Deep Learning - Business Case Example/1. Business Case Exploring the Dataset and Identifying Predictors.mp4 66.27 MB
51. Deep Learning - Business Case Example/11. Business Case Testing the Model.mp4 10.79 MB
51. Deep Learning - Business Case Example/2. Business Case Outlining the Solution.mp4 7.3 MB
51. Deep Learning - Business Case Example/3. Business Case Balancing the Dataset.mp4 30.43 MB
51. Deep Learning - Business Case Example/4. Business Case Preprocessing the Data.mp4 84.33 MB
51. Deep Learning - Business Case Example/6. Business Case Load the Preprocessed Data.mp4 17.57 MB
51. Deep Learning - Business Case Example/8. Business Case Learning and Interpreting the Result.mp4 31.18 MB
51. Deep Learning - Business Case Example/9. Business Case Setting an Early Stopping Mechanism.mp4 49.81 MB
52. Deep Learning - Conclusion/1. Summary on What You've Learned.mp4 39.75 MB
52. Deep Learning - Conclusion/2. What's Further out there in terms of Machine Learning.mp4 20.13 MB
52. Deep Learning - Conclusion/4. An overview of CNNs.mp4 58.79 MB
52. Deep Learning - Conclusion/5. An Overview of RNNs.mp4 25.26 MB
52. Deep Learning - Conclusion/6. An Overview of non-NN Approaches.mp4 44.77 MB
53. Appendix Deep Learning - TensorFlow 1 Introduction/2. How to Install TensorFlow 1.mp4 11.35 MB
53. Appendix Deep Learning - TensorFlow 1 Introduction/4. TensorFlow Intro.mp4 47.69 MB
53. Appendix Deep Learning - TensorFlow 1 Introduction/5. Actual Introduction to TensorFlow.mp4 17.42 MB
53. Appendix Deep Learning - TensorFlow 1 Introduction/6. Types of File Formats, supporting Tensors.mp4 20.34 MB
53. Appendix Deep Learning - TensorFlow 1 Introduction/7. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.mp4 38.49 MB
53. Appendix Deep Learning - TensorFlow 1 Introduction/8. Basic NN Example with TF Loss Function and Gradient Descent.mp4 32.51 MB
53. Appendix Deep Learning - TensorFlow 1 Introduction/9. Basic NN Example with TF Model Output.mp4 37.39 MB
54. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/1. MNIST What is the MNIST Dataset.mp4 17.82 MB
54. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/2. MNIST How to Tackle the MNIST.mp4 22.58 MB
54. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/3. MNIST Relevant Packages.mp4 18.9 MB
54. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/4. MNIST Model Outline.mp4 56.38 MB
54. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/5. MNIST Loss and Optimization Algorithm.mp4 25.86 MB
54. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/6. Calculating the Accuracy of the Model.mp4 43.9 MB
54. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/7. MNIST Batching and Early Stopping.mp4 12.86 MB
54. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/8. MNIST Learning.mp4 46.68 MB
54. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/9. MNIST Results and Testing.mp4 62.77 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/1. Business Case Getting Acquainted with the Dataset.mp4 87.65 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/10. Business Case Testing the Model.mp4 11.2 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/11. Business Case A Comment on the Homework.mp4 36.39 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/2. Business Case Outlining the Solution.mp4 12.21 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/3. The Importance of Working with a Balanced Dataset.mp4 39.41 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/4. Business Case Preprocessing.mp4 103.41 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/6. Creating a Data Provider.mp4 76.34 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/7. Business Case Model Outline.mp4 53.13 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/8. Business Case Optimization.mp4 41.52 MB
55. Appendix Deep Learning - TensorFlow 1 Business Case/9. Business Case Interpretation.mp4 25.74 MB
56. Software Integration/1. What are Data, Servers, Clients, Requests, and Responses.mp4 69.03 MB
56. Software Integration/3. What are Data Connectivity, APIs, and Endpoints.mp4 104.08 MB
56. Software Integration/5. Taking a Closer Look at APIs.mp4 115.59 MB
56. Software Integration/7. Communication between Software Products through Text Files.mp4 60.34 MB
56. Software Integration/9. Software Integration - Explained.mp4 63.69 MB
57. Case Study - What's Next in the Course/1. Game Plan for this Python, SQL, and Tableau Business Exercise.mp4 52.3 MB
57. Case Study - What's Next in the Course/2. The Business Task.mp4 39.15 MB
57. Case Study - What's Next in the Course/3. Introducing the Data Set.mp4 40.87 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/10. Analyzing the Reasons for Absence.mp4 40.57 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/11. Obtaining Dummies from a Single Feature.mp4 81.12 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/15. More on Dummy Variables A Statistical Perspective.mp4 13.74 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/16. Classifying the Various Reasons for Absence.mp4 74.6 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/17. Using .concat() in Python.mp4 38.73 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/2. Importing the Absenteeism Data in Python.mp4 23.15 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/20. Reordering Columns in a Pandas DataFrame in Python.mp4 14.02 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/23. Creating Checkpoints while Coding in Jupyter.mp4 25.67 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/26. Analyzing the Dates from the Initial Data Set.mp4 57.28 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/27. Extracting the Month Value from the Date Column.mp4 47.79 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/28. Extracting the Day of the Week from the Date Column.mp4 27.96 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/3. Checking the Content of the Data Set.mp4 61.9 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/30. Analyzing Several Straightforward Columns for this Exercise.mp4 29.51 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/31. Working on Education, Children, and Pets.mp4 39.59 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/32. Final Remarks of this Section.mp4 21.63 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/4. Introduction to Terms with Multiple Meanings.mp4 27.86 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/6. Using a Statistical Approach towards the Solution to the Exercise.mp4 20.19 MB
58. Case Study - Preprocessing the 'Absenteeism_data'/7. Dropping a Column from a DataFrame in Python.mp4 61.76 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/1. Exploring the Problem with a Machine Learning Mindset.mp4 27.55 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/10. Interpreting the Coefficients of the Logistic Regression.mp4 40.4 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/11. Backward Elimination or How to Simplify Your Model.mp4 39.56 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/12. Testing the Model We Created.mp4 49.06 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/13. Saving the Model and Preparing it for Deployment.mp4 37.45 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/16. Preparing the Deployment of the Model through a Module.mp4 44.49 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/2. Creating the Targets for the Logistic Regression.mp4 45.79 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/3. Selecting the Inputs for the Logistic Regression.mp4 16.75 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/4. Standardizing the Data.mp4 20.59 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/5. Splitting the Data for Training and Testing.mp4 52.76 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/6. Fitting the Model and Assessing its Accuracy.mp4 41.62 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/7. Creating a Summary Table with the Coefficients and Intercept.mp4 38.87 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/8. Interpreting the Coefficients for Our Problem.mp4 52.37 MB
59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/9. Standardizing only the Numerical Variables (Creating a Custom Scaler).mp4 41.19 MB
6. The Field of Data Science - Popular Data Science Tools/1. Necessary Programming Languages and Software Used in Data Science.mp4 103.51 MB
60. Case Study - Loading the 'absenteeism_module'/2. Deploying the 'absenteeism_module' - Part I.mp4 25.48 MB
60. Case Study - Loading the 'absenteeism_module'/3. Deploying the 'absenteeism_module' - Part II.mp4 54.26 MB
61. Case Study - Analyzing the Predicted Outputs in Tableau/2. Analyzing Age vs Probability in Tableau.mp4 56.55 MB
61. Case Study - Analyzing the Predicted Outputs in Tableau/4. Analyzing Reasons vs Probability in Tableau.mp4 59.33 MB
61. Case Study - Analyzing the Predicted Outputs in Tableau/6. Analyzing Transportation Expense vs Probability in Tableau.mp4 40.63 MB
62. Appendix - Additional Python Tools/1. Using the .format() Method.mp4 47.64 MB
62. Appendix - Additional Python Tools/2. Iterating Over Range Objects.mp4 22.49 MB
62. Appendix - Additional Python Tools/3. Introduction to Nested For Loops.mp4 29.46 MB
62. Appendix - Additional Python Tools/4. Triple Nested For Loops.mp4 46.6 MB
62. Appendix - Additional Python Tools/5. List Comprehensions.mp4 55.45 MB
62. Appendix - Additional Python Tools/6. Anonymous (Lambda) Functions.mp4 38.54 MB
7. The Field of Data Science - Careers in Data Science/1. Finding the Job - What to Expect and What to Look for.mp4 54.38 MB
8. The Field of Data Science - Debunking Common Misconceptions/1. Debunking Common Misconceptions.mp4 72.85 MB
9. Part 2 Probability/1. The Basic Probability Formula.mp4 85.92 MB
9. Part 2 Probability/3. Computing Expected Values.mp4 75.68 MB
9. Part 2 Probability/5. Frequency.mp4 61.73 MB
9. Part 2 Probability/7. Events and Their Complements.mp4 59.15 MB
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