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[GigaCourse.com] Udemy - Deep Learning with Keras and Tensorflow in Python and R
magnet:?xt=urn:btih:a24dc0ed8c01e123276ab97f1f6716e974dd2995&dn=[GigaCourse.com] Udemy - Deep Learning with Keras and Tensorflow in Python and R
磁力链接详情
Hash值:
a24dc0ed8c01e123276ab97f1f6716e974dd2995
点击数:
221
文件大小:
4 GB
文件数量:
72
创建日期:
2020-11-23 09:36
最后访问:
2024-6-22 12:04
访问标签:
GigaCourse
com
Udemy
-
Deep
Learning
with
Keras
and
Tensorflow
in
Python
and
R
文件列表详情
1. Introduction/1. Introduction.mp4 29.1 MB
10. Python - Building and training the Model/1. Different ways to create ANN using Keras.mp4 10.81 MB
10. Python - Building and training the Model/2. Building the Neural Network using Keras.mp4 79.15 MB
10. Python - Building and training the Model/3. Compiling and Training the Neural Network model.mp4 81.66 MB
10. Python - Building and training the Model/4. Evaluating performance and Predicting using Keras.mp4 69.87 MB
11. R - Building and training the Model/1. Building,Compiling and Training.mp4 130.73 MB
11. R - Building and training the Model/2. Evaluating and Predicting.mp4 99.26 MB
12. Python - Regression problems and Functional API/1. Building Neural Network for Regression Problem.mp4 155.87 MB
12. Python - Regression problems and Functional API/2. Using Functional API for complex architectures.mp4 92.14 MB
13. R - Regression Problem and Functional API/1. Building Regression Model with Functional AP.mp4 131.14 MB
13. R - Regression Problem and Functional API/2. Complex Architectures using Functional API.mp4 79.58 MB
14. Python - Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 151.63 MB
15. R - Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 216.1 MB
16. Python - Hyperparameter Tuning/1. Hyperparameter Tuning.mp4 60.64 MB
17. R - Hyperparameter Tuning/1. Hyperparameter Tuning.mp4 60.63 MB
18. Add on Data Preprocessing/1. Gathering Business Knowledge.mp4 22.29 MB
18. Add on Data Preprocessing/10. Outlier Treatment in Python.mp4 70.24 MB
18. Add on Data Preprocessing/11. Outlier Treatment in R.mp4 30.75 MB
18. Add on Data Preprocessing/12. Missing Value imputation.mp4 24.99 MB
18. Add on Data Preprocessing/13. Missing Value Imputation in Python.mp4 23.42 MB
18. Add on Data Preprocessing/14. Missing Value imputation in R.mp4 26 MB
18. Add on Data Preprocessing/15. Seasonality in Data.mp4 17.04 MB
18. Add on Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.mp4 100.47 MB
18. Add on Data Preprocessing/17. Variable transformation and deletion in Python.mp4 44.12 MB
18. Add on Data Preprocessing/18. Variable transformation in R.mp4 55.43 MB
18. Add on Data Preprocessing/19. Non Usable Variables.mp4 20.25 MB
18. Add on Data Preprocessing/2. Data Exploration.mp4 20.51 MB
18. Add on Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp4 36.84 MB
18. Add on Data Preprocessing/21. Dummy variable creation in Python.mp4 26.53 MB
18. Add on Data Preprocessing/22. Dummy variable creation in R.mp4 43.97 MB
18. Add on Data Preprocessing/3. The Data and the Data Dictionary.mp4 69.34 MB
18. Add on Data Preprocessing/4. Importing Data in Python.mp4 27.84 MB
18. Add on Data Preprocessing/5. Importing the dataset into R.mp4 13.1 MB
18. Add on Data Preprocessing/6. Univariate Analysis and EDD.mp4 24.2 MB
18. Add on Data Preprocessing/7. EDD in Python.mp4 61.78 MB
18. Add on Data Preprocessing/8. EDD in R.mp4 96.98 MB
18. Add on Data Preprocessing/9. Outlier Treatment.mp4 24.48 MB
19. Test Train Split/1. Test-train split.mp4 41.87 MB
19. Test Train Split/2. Bias Variance trade-off.mp4 25.1 MB
19. Test Train Split/3. Test train split in Python.mp4 44.87 MB
19. Test Train Split/4. Test train split in R.mp4 75.62 MB
2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.mp4 16.28 MB
2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp4 65.2 MB
2. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.mp4 40.92 MB
2. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.mp4 12.75 MB
2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4 64.44 MB
2. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.mp4 60.32 MB
2. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.mp4 43.89 MB
2. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.mp4 46.89 MB
2. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.mp4 40.35 MB
3. Setting up R Studio and R Crash Course/1. Installing R and R studio.mp4 35.7 MB
3. Setting up R Studio and R Crash Course/2. Basics of R and R studio.mp4 38.85 MB
3. Setting up R Studio and R Crash Course/3. Packages in R.mp4 82.95 MB
3. Setting up R Studio and R Crash Course/4. Inputting data part 1 Inbuilt datasets of R.mp4 40.73 MB
3. Setting up R Studio and R Crash Course/5. Inputting data part 2 Manual data entry.mp4 25.52 MB
3. Setting up R Studio and R Crash Course/6. Inputting data part 3 Importing from CSV or Text files.mp4 60.07 MB
3. Setting up R Studio and R Crash Course/7. Creating Barplots in R.mp4 96.76 MB
3. Setting up R Studio and R Crash Course/8. Creating Histograms in R.mp4 42.01 MB
4. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.mp4 44.75 MB
4. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.mp4 34.63 MB
4. Single Cells - Perceptron and Sigmoid Neuron/3. Python - Creating Perceptron model.mp4 86.59 MB
5. Neural Networks - Stacking cells to create network/1. Basic Terminologies.mp4 40.43 MB
5. Neural Networks - Stacking cells to create network/2. Gradient Descent.mp4 60.34 MB
5. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 122.2 MB
6. Important concepts Common Interview questions/1. Some Important Concepts.mp4 62.18 MB
7. Standard Model Parameters/1. Hyperparameters.mp4 45.35 MB
8. Tensorflow and Keras/1. Keras and Tensorflow.mp4 14.92 MB
8. Tensorflow and Keras/2. Installing Tensorflow and Keras in Python.mp4 20.06 MB
8. Tensorflow and Keras/3. Installing TensorFlow and Keras in R.mp4 22.83 MB
9. Dataset for classification problem/1. Python - Dataset for classification problem.mp4 56.18 MB
9. Dataset for classification problem/2. Python - Normalization and Test-Train split.mp4 44.21 MB
9. Dataset for classification problem/3. R - Dataset, Normalization and Test-Train set.mp4 111.81 MB
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