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种子名称： [DesireCourse.Net] Udemy - Complete Tensorflow 2 and Keras Deep Learning Bootcamp
文件类型： 视频
文件数目： 114个文件
文件大小： 6.55 GB
收录时间： 2020-1-10 11:13
已经下载： 3次
资源热度： 174
最近下载： 2024-12-22 11:43

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[DesireCourse.Net] Udemy - Complete Tensorflow 2 and Keras Deep Learning Bootcamp.torrent

1. Course Overview, Installs, and Setup/1. Course Overview.mp426.16MB

1. Course Overview, Installs, and Setup/2. Course Setup and Installation.mp4152.41MB

10. Natural Language Processing/1. Introduction to NLP Section.mp435.12MB

10. Natural Language Processing/2. NLP - Part One - The Data.mp422.29MB

10. Natural Language Processing/3. NLP - Part Two - Text Processing.mp422.88MB

10. Natural Language Processing/4. NLP - Part Three - Creating Batches.mp481.69MB

10. Natural Language Processing/5. NLP - Part Four - Creating the Model.mp464.31MB

10. Natural Language Processing/6. NLP - Part Five - Training the Model.mp465.26MB

10. Natural Language Processing/7. NLP - Part Six - Generating Text.mp452.3MB

11. AutoEncoders/1. Introduction to Autoencoders.mp420.88MB

11. AutoEncoders/2. Autoencoder Basics.mp442.64MB

11. AutoEncoders/3. Autoencoder for Dimensionality Reduction.mp4117.47MB

11. AutoEncoders/4. Autoencoder for Images - Part One.mp494.09MB

11. AutoEncoders/5. Autoencoder for Images - Part Two - Noise Removal.mp460.51MB

11. AutoEncoders/6. Autoencoder Exercise Overview.mp433.92MB

11. AutoEncoders/7. Autoencoder Exercise - Solutions.mp477.76MB

12. Generative Adversarial Networks/1. GANs Overview.mp453.86MB

12. Generative Adversarial Networks/2. Creating a GAN - Part One- The Data.mp419.12MB

12. Generative Adversarial Networks/3. Creating a GAN - Part Two - The Model.mp469.8MB

12. Generative Adversarial Networks/4. Creating a GAN - Part Three - Model Training.mp4131.58MB

12. Generative Adversarial Networks/5. DCGAN - Deep Convolutional Generative Adversarial Networks.mp457.17MB

13. Deployment/1. Introduction to Deployment.mp423.43MB

13. Deployment/2. Creating the Model.mp487.07MB

13. Deployment/3. Model Prediction Function.mp453.03MB

13. Deployment/4. Running a Basic Flask Application.mp462.02MB

13. Deployment/5. Flask Postman API.mp469.11MB

13. Deployment/6. Flask API - Using Requests Programmatically.mp419.9MB

13. Deployment/7. Flask Front End.mp4149.59MB

13. Deployment/8. Live Deployment to the Web.mp4126.54MB

3. NumPy Crash Course/1. Introduction to NumPy.mp411.38MB

3. NumPy Crash Course/2. NumPy Arrays.mp488.58MB

3. NumPy Crash Course/3. Numpy Index Selection.mp446.37MB

3. NumPy Crash Course/4. NumPy Operations.mp448.6MB

3. NumPy Crash Course/5. NumPy Exercises.mp411.51MB

3. NumPy Crash Course/6. Numpy Exercises - Solutions.mp448.59MB

4. Pandas Crash Course/1. Introduction to Pandas.mp425.5MB

4. Pandas Crash Course/10. Pandas Exercises - Solutions.mp451.46MB

4. Pandas Crash Course/2. Pandas Series.mp437.88MB

4. Pandas Crash Course/3. Pandas DataFrames - Part One.mp445.17MB

4. Pandas Crash Course/4. Pandas DataFrames - Part Two.mp437.01MB

4. Pandas Crash Course/5. Pandas Missing Data.mp444.06MB

4. Pandas Crash Course/6. GroupBy Operations.mp456.37MB

4. Pandas Crash Course/7. Pandas Operations.mp461.21MB

4. Pandas Crash Course/8. Data Input and Output.mp493.48MB

4. Pandas Crash Course/9. Pandas Exercises.mp423.48MB

5. Visualization Crash Course/1. Introduction to Python Visualization.mp46.82MB

5. Visualization Crash Course/2. Matplotlib Basics.mp441.03MB

5. Visualization Crash Course/3. Seaborn Basics.mp491.85MB

5. Visualization Crash Course/4. Data Visualization Exercises.mp422.82MB

5. Visualization Crash Course/5. Data Visualization Exercises - Solutions.mp450.46MB

6. Machine Learning Concepts Overview/1. What is Machine Learning.mp428.2MB

6. Machine Learning Concepts Overview/2. Supervised Learning Overview.mp440.03MB

6. Machine Learning Concepts Overview/3. Overfitting.mp426.31MB

6. Machine Learning Concepts Overview/4. Evaluating Performance - Classification Error Metrics.mp482.69MB

6. Machine Learning Concepts Overview/5. Evaluating Performance - Regression Error Metrics.mp423.69MB

6. Machine Learning Concepts Overview/6. Unsupervised Learning.mp418.82MB

7. Basic Artificial Neural Networks - ANNs/1. Introduction to ANN Section.mp49.7MB

7. Basic Artificial Neural Networks - ANNs/10. Keras Syntax Basics - Part Two - Creating and Training the Model.mp484.64MB

7. Basic Artificial Neural Networks - ANNs/11. Keras Syntax Basics - Part Three - Model Evaluation.mp464.96MB

7. Basic Artificial Neural Networks - ANNs/12. Keras Regression Code Along - Exploratory Data Analysis.mp4137.06MB

7. Basic Artificial Neural Networks - ANNs/13. Keras Regression Code Along - Exploratory Data Analysis - Continued.mp476.18MB

7. Basic Artificial Neural Networks - ANNs/14. Keras Regression Code Along - Data Preprocessing and Creating a Model.mp447.01MB

7. Basic Artificial Neural Networks - ANNs/15. Keras Regression Code Along - Model Evaluation and Predictions.mp468.91MB

7. Basic Artificial Neural Networks - ANNs/16. Keras Classification Code Along - EDA and Preprocessing.mp456.15MB

7. Basic Artificial Neural Networks - ANNs/17. Keras Classification - Dealing with Overfitting and Evaluation.mp4111.25MB

7. Basic Artificial Neural Networks - ANNs/18. TensorFlow 2.0 Keras Project Options Overview.mp47.86MB

7. Basic Artificial Neural Networks - ANNs/19. TensorFlow 2.0 Keras Project Notebook Overview.mp480.56MB

7. Basic Artificial Neural Networks - ANNs/2. Perceptron Model.mp447.8MB

7. Basic Artificial Neural Networks - ANNs/20. Keras Project Solutions - Exploratory Data Analysis.mp4143.63MB

7. Basic Artificial Neural Networks - ANNs/21. Keras Project Solutions - Dealing with Missing Data.mp496.78MB

7. Basic Artificial Neural Networks - ANNs/22. Keras Project Solutions - Dealing with Missing Data - Part Two.mp485.4MB

7. Basic Artificial Neural Networks - ANNs/23. Keras Project Solutions - Categorical Data.mp4125.03MB

7. Basic Artificial Neural Networks - ANNs/24. Keras Project Solutions - Data PreProcessing.mp423.95MB

7. Basic Artificial Neural Networks - ANNs/25. Keras Project Solutions - Creating and Training a Model.mp429.72MB

7. Basic Artificial Neural Networks - ANNs/26. Keras Project Solutions - Model Evaluation.mp463.17MB

7. Basic Artificial Neural Networks - ANNs/27. Tensorboard.mp4144.18MB

7. Basic Artificial Neural Networks - ANNs/3. Neural Networks.mp435.79MB

7. Basic Artificial Neural Networks - ANNs/4. Activation Functions.mp462.52MB

7. Basic Artificial Neural Networks - ANNs/5. Multi-Class Classification Considerations.mp445.9MB

7. Basic Artificial Neural Networks - ANNs/6. Cost Functions and Gradient Descent.mp475.67MB

7. Basic Artificial Neural Networks - ANNs/7. Backpropagation.mp457.68MB

7. Basic Artificial Neural Networks - ANNs/8. TensorFlow vs. Keras Explained.mp410.47MB

7. Basic Artificial Neural Networks - ANNs/9. Keras Syntax Basics - Part One - Preparing the Data.mp450.5MB

8. Convolutional Neural Networks - CNNs/1. CNN Section Overview.mp47.52MB

8. Convolutional Neural Networks - CNNs/10. CNN on CIFAR-10 - Part Two - Evaluating the Model.mp445.34MB

8. Convolutional Neural Networks - CNNs/11. Downloading Data Set for Real Image Lectures.mp428.23MB

8. Convolutional Neural Networks - CNNs/12. CNN on Real Image Files - Part One - Reading in the Data.mp480.69MB

8. Convolutional Neural Networks - CNNs/13. CNN on Real Image Files - Part Two - Data Processing.mp487.92MB

8. Convolutional Neural Networks - CNNs/14. CNN on Real Image Files - Part Three - Creating the Model.mp490.63MB

8. Convolutional Neural Networks - CNNs/15. CNN on Real Image Files - Part Four - Evaluating the Model.mp447.11MB

8. Convolutional Neural Networks - CNNs/16. CNN Exercise Overview.mp417.88MB

8. Convolutional Neural Networks - CNNs/17. CNN Exercise Solutions.mp456.02MB

8. Convolutional Neural Networks - CNNs/2. Image Filters and Kernels.mp472.34MB

8. Convolutional Neural Networks - CNNs/3. Convolutional Layers.mp458MB

8. Convolutional Neural Networks - CNNs/4. Pooling Layers.mp427.65MB

8. Convolutional Neural Networks - CNNs/5. MNIST Data Set Overview.mp421.11MB

8. Convolutional Neural Networks - CNNs/6. CNN on MNIST - Part One - The Data.mp459.82MB

8. Convolutional Neural Networks - CNNs/7. CNN on MNIST - Part Two - Creating and Training the Model.mp498.92MB

8. Convolutional Neural Networks - CNNs/8. CNN on MNIST - Part Three - Model Evaluation.mp438.48MB

8. Convolutional Neural Networks - CNNs/9. CNN on CIFAR-10 - Part One - The Data.mp464.31MB

9. Recurrent Neural Networks - RNNs/1. RNN Section Overview.mp410.91MB

9. Recurrent Neural Networks - RNNs/10. RNN on a Time Series - Part One.mp445.01MB

9. Recurrent Neural Networks - RNNs/11. RNN on a Time Series - Part Two.mp4131.02MB

9. Recurrent Neural Networks - RNNs/12. RNN Exercise.mp429.92MB

9. Recurrent Neural Networks - RNNs/13. RNN Exercise - Solutions.mp4148.08MB

9. Recurrent Neural Networks - RNNs/14. Bonus - Multivariate Time Series - RNN and LSTMs.mp4149.33MB

9. Recurrent Neural Networks - RNNs/2. RNN Basic Theory.mp429.97MB

9. Recurrent Neural Networks - RNNs/3. Vanishing Gradients.mp428.12MB

9. Recurrent Neural Networks - RNNs/4. LSTMS and GRU.mp441.94MB

9. Recurrent Neural Networks - RNNs/5. RNN Batches.mp432.72MB

9. Recurrent Neural Networks - RNNs/6. RNN on a Sine Wave - The Data.mp440.13MB

9. Recurrent Neural Networks - RNNs/7. RNN on a Sine Wave - Batch Generator.mp450.03MB

9. Recurrent Neural Networks - RNNs/8. RNN on a Sine Wave - Creating the Model.mp483.8MB

9. Recurrent Neural Networks - RNNs/9. RNN on a Sine Wave - LSTMs and Forecasting.mp483.49MB