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- 01-welcome-to-the-course/004-installation-video-guide.mp4 47.4 MB
- 03-machine-learning/045-exercise-2-solution.mp4 45.3 MB
- 03-machine-learning/031-linear-regression-code-along.mp4 41.8 MB
- 03-machine-learning/043-exercise-1-solution.mp4 39.1 MB
- 04-deep-learning-intro/051-multiclass-classification-code-along.mp4 35.6 MB
- 05-gradient-descent/070-learning-rate-code-along.mp4 34.8 MB
- 01-welcome-to-the-course/007-your-first-deep-learning-model.mp4 34.5 MB
- 02-data/011-plotting-with-matplotlib.mp4 34.4 MB
- 05-gradient-descent/077-inner-layers-visualization-code-along.mp4 33.8 MB
- 02-data/009-data-exploration-with-pandas-code-along.mp4 32.4 MB
- 09-improving-performance/131-movies-reviews-sentiment-analysis-code-along.mp4 28.0 MB
- 04-deep-learning-intro/057-exercise-2-solution.mp4 26.4 MB
- 04-deep-learning-intro/055-exercise-1-solution.mp4 26.0 MB
- 01-welcome-to-the-course/002-real-world-applications-of-deep-learning.mp4 24.7 MB
- 03-machine-learning/035-classification-code-along.mp4 24.0 MB
- 08-recurrent-neural-networks/116-rolling-windows-code-along.mp4 22.1 MB
- 04-deep-learning-intro/049-neural-networks-code-along.mp4 22.1 MB
- 04-deep-learning-intro/059-exercise-3-solution.mp4 21.6 MB
- 06-convolutional-neural-networks/089-mnist-classification-code-along.mp4 20.6 MB
- 05-gradient-descent/068-numpy-arrays-code-along.mp4 20.4 MB
- 2. Working with the Keras Functional API/CNNs and Basic Image Classification - Mastering Keras [Video].mp4 252.4 MB
- 3. Developing and Implementing Deep Generative Models/Implementing VAEs in Keras - Mastering Keras [Video].mp4 65.5 MB
- 7. One-Shot and Deep Semi-Supervised Learning/Siamese Networks - Mastering Keras [Video].mp4 56.5 MB
- 3. Developing and Implementing Deep Generative Models/Implementing GANs in Keras - Mastering Keras [Video].mp4 54.5 MB
- 2. Working with the Keras Functional API/MLPs and Simple Data Analytics - Mastering Keras [Video].mp4 54.0 MB
- 2. Working with the Keras Functional API/RNNs and Sequential Data Analysis - Mastering Keras [Video].mp4 52.6 MB
- 6. Deep Reinforcement Learning/(Epsilon) Q-Learning and Deep Q-Networks - Mastering Keras [Video].mp4 51.5 MB
- 6. Deep Reinforcement Learning/Dealing with Instability (1)- Experiential Replay - Mastering Keras [Video].mp4 45.1 MB
- 6. Deep Reinforcement Learning/Advantage Networks - Mastering Keras [Video].mp4 42.4 MB
- 4. Advanced CNNs/Residual Networks-Layers - Mastering Keras [Video].mp4 40.1 MB
- 4. Advanced CNNs/Working with Inception Networks- Layers - Mastering Keras [Video].mp4 35.1 MB
- 2. Working with the Keras Functional API/AEs and Denoising Data - Mastering Keras [Video].mp4 30.5 MB
- 6. Deep Reinforcement Learning/Dealing with Instability (2)- Double Deep Q-Networks - Mastering Keras [Video].mp4 27.8 MB
- 4. Advanced CNNs/Dense Networks - Mastering Keras [Video].mp4 27.7 MB
- 4. Advanced CNNs/Transfer Learning- Applying Advanced Architectures on Real Data - Mastering Keras [Video].mp4 25.4 MB
- 5. Object Detection/Fast RCNNs - Mastering Keras [Video].mp4 22.8 MB
- 5. Object Detection/Region Proposal Networks and Faster RCNNs - Mastering Keras [Video].mp4 22.7 MB
- 1. Preparing Yourself for Mastering Keras Journey/Setting Up the Environment and Teaching Methodology.mp4 21.1 MB
- 6. Deep Reinforcement Learning/Reinforcement Learning Basics - Mastering Keras [Video].mp4 20.5 MB
- 7. One-Shot and Deep Semi-Supervised Learning/Semi-Supervised Learning Using GANs - Mastering Keras [Video].mp4 20.1 MB
- 1. Cold Iron Light.flac 51.4 MB
- 8. Keras.flac 44.7 MB
- 7. Low Winter Sun.flac 42.9 MB
- 6. October Dawn.flac 40.6 MB
- 3. Black Square Icon.flac 38.1 MB
- 4. The Wood Demon.flac 36.0 MB
- 2. Temple of Zaum.flac 30.0 MB
- 5. Move 37.flac 27.8 MB
- Cracked Machine - Gates of Keras (2020) [FLAC].cuetools.flac.cue 652 Bytes
- GetFreeCourses.Co-Udemy-CNN for Computer Vision with Keras and TensorFlow in Python.zip 2.6 GB
- 11. Python - Solving a Regression problem using ANN/1. Building Neural Network for Regression Problem.mp4 163.5 MB
- 13. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 158.9 MB
- 4. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 128.1 MB
- 15. Add-on 1 Data Preprocessing/12. Bi-variate analysis and Variable transformation.mp4 105.3 MB
- 16. Add-on 2 Classic ML models - Linear Regression/3. Assessing accuracy of predicted coefficients.mp4 96.6 MB
- 12. Complex ANN Architectures using Functional API/1. Using Functional API for complex architectures.mp4 96.6 MB
- 3. Single Cells - Perceptron and Sigmoid Neuron/3. Python - Creating Perceptron model.mp4 90.8 MB
- 10. Python - Building and training the Model/3. Compiling and Training the Neural Network model.mp4 85.7 MB
- 10. Python - Building and training the Model/2. Building the Neural Network using Keras.mp4 83.0 MB
- 15. Add-on 1 Data Preprocessing/17. Correlation Analysis.mp4 75.1 MB
- 15. Add-on 1 Data Preprocessing/8. Outlier Treatment in Python.mp4 73.6 MB
- 10. Python - Building and training the Model/4. Evaluating performance and Predicting using Keras.mp4 73.3 MB
- 16. Add-on 2 Classic ML models - Linear Regression/9. Multiple Linear Regression in Python.mp4 73.1 MB
- 15. Add-on 1 Data Preprocessing/3. The Dataset and the Data Dictionary.mp4 72.7 MB
- 2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp4 68.3 MB
- 2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4 67.6 MB
- 16. Add-on 2 Classic ML models - Linear Regression/5. Simple Linear Regression in Python.mp4 66.5 MB
- 5. Important concepts Common Interview questions/1. Some Important Concepts.mp4 65.2 MB
- 15. Add-on 1 Data Preprocessing/6. EDD in Python.mp4 64.8 MB
- 14. Hyperparameter Tuning/1. Hyperparameter Tuning.mp4 63.6 MB
- Geron A. - Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd edition - 2019.pdf 56.6 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
- 1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.srt 147.0 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
- 7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
- 2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
- 7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
- 15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
- 7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
- 15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
- 7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
- 7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
- 7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
- [ FreeCourseWeb.com ] Udemy - Natural Language Processing(NLP) with Deep Learning in Keras.zip 4.2 GB
- Code.zip 97.4 MB
- Mosconi F. Zero to Deep Learning with Keras and Tensorflow 2020.pdf 35.2 MB
- Artificial Intelligence #5 MLP Networks with Scikit & Keras.zip 921.6 MB
- Download more courses.url 123 Bytes
- Downloaded from TutsGalaxy.com.txt 73 Bytes
- TutsGalaxy.com.txt 52 Bytes
- 16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
- 1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.srt 147.0 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
- 7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
- 2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
- 7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
- 15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
- 7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
- 15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
- 7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
- 7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
- 7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
- 11. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 226.7 MB
- 9. R - Building and training the Model/1. Building, Compiling and Training.mp4 137.1 MB
- 4. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 128.1 MB
- 8. R - Dataset for classification problem/1. Data Normalization and Test-Train Split.mp4 117.2 MB
- 19. Transfer Learning in R/1. Project - Transfer Learning - VGG16 (Implementation).mp4 106.5 MB
- 9. R - Building and training the Model/2. Evaluating and Predicting.mp4 104.0 MB
- 2. Setting Up R Studio and R crash course/7. Creating Barplots in R.mp4 101.4 MB
- 16. Project Creating CNN model from scratch/3. Project in R - Data Preprocessing.mp4 92.0 MB
- 10. The NeuralNets Package/1. ANN with NeuralNets Package.mp4 88.5 MB
- 2. Setting Up R Studio and R crash course/3. Packages in R.mp4 87.0 MB
- 14. Creating CNN model in R/3. Creating Model Architecture.mp4 75.1 MB
- 14. Creating CNN model in R/5. Model Performance.mp4 71.4 MB
- 13. CNN - Basics/5. Channels.mp4 71.1 MB
- 14. Creating CNN model in R/2. Data Preprocessing.mp4 70.3 MB
- 19. Transfer Learning in R/2. Project - Transfer Learning - VGG16 (Performance).mp4 67.3 MB
- 5. Important concepts Common Interview questions/1. Some Important Concepts.mp4 65.2 MB
- 12. Hyperparameter Tuning/1. Hyperparameter Tuning.mp4 63.6 MB
- 4. Neural Networks - Stacking cells to create network/2. Gradient Descent.mp4 63.3 MB
- 2. Setting Up R Studio and R crash course/6. Inputting data part 3 Importing from CSV or Text files.mp4 63.0 MB
- 17. Project Data Augmentation for avoiding overfitting/1. Project in R - Data Augmentation.mp4 59.1 MB
- [ FreeCourseWeb.com ] Udemy - Artificial Intelligence #5- MLP Networks with Scikit & Keras (Updated).rar 887.6 MB
- Tensorflow and Keras For Neural Networks and Deep Learning.zip 5.3 GB
- Download more courses.url 123 Bytes
- Downloaded from TutsGalaxy.com.txt 73 Bytes
- TutsGalaxy.com.txt 52 Bytes
- Библиотека Keras - инструмент глубокого обучения.pdf 61.2 MB
- [DMC.RIP] Сперва прочти!.docx 270.0 kB
- DMC.RIP - трекер с курсами.url 106 Bytes
- [DesireCourse.Com] Udemy - Zero to Deep Learning™ with Python and Keras.zip 1.3 GB
- [DesireCourse.Com].txt 828 Bytes
- [DesireCourse.Com].url 51 Bytes
- 00.Course-Overview/00.Course-Overview.mp4 3.8 MB
- 00.Course-Overview/00.Course-Overview.mp4.srt 2.1 kB
- 00.Course-Overview/clips-info.json 253 Bytes
- 00.Course-Overview/module-info.json 284 Bytes
- 01.Introducing-Keras/00.Introduction.mp4 2.1 MB
- 01.Introducing-Keras/00.Introduction.mp4.srt 1.4 kB
- 01.Introducing-Keras/01.What-Is-Keras.mp4 3.7 MB
- 01.Introducing-Keras/01.What-Is-Keras.mp4.srt 4.0 kB
- 01.Introducing-Keras/02.Neural-Networks.mp4 8.5 MB
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- 01.Introducing-Keras/03.Skills.mp4 4.6 MB
- 01.Introducing-Keras/03.Skills.mp4.srt 4.6 kB
- 01.Introducing-Keras/04.Course-Structure.mp4 2.9 MB
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- 02.Creating-Your-First-Neural-Network-with-Keras/00.Introduction-to-Installation.mp4 4.9 MB
- 02.Creating-Your-First-Neural-Network-with-Keras/00.Introduction-to-Installation.mp4.srt 3.6 kB
- 02.Creating-Your-First-Neural-Network-with-Keras/01.Installing-TensorFlow.mp4 22.0 MB
- 02.Creating-Your-First-Neural-Network-with-Keras/01.Installing-TensorFlow.mp4.srt 6.4 kB
- video3_9.mp4 33.7 MB
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- video3_8.mp4 15.2 MB
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- 08-recurrent-neural-networks/110-vanishing-gradients.html 331 Bytes
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- 09-improving-performance/132-exercise-1-solution.html 331 Bytes
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- 02-data/021-exercise-4-presentation.mp4 1.6 MB
- 02-data/019-exercise-3-presentation.mp4 1.8 MB
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- Джулли А.,Пал С. - Библиотека Keras - инструмент глубокого обучения - 2018.PDF 61.2 MB