[Udemy] Practical AI with Python and Reinforcement Learning (07.2021)

Creation Time	July 13, 2024, 1:25 a.m.
Last Access Time	Oct. 30, 2025, 7:13 a.m.
File Size	7.4 GB
Keywords	and 07 AI Reinforcement Udemy Practical Python 2021 Learning with
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Total Files	251
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11 Classical Q Learning/019 Q-Learning Exercise Project - Solutions.mp4 177.1 MB
10 Open AI Gym Overview/003 OpenAI Gym - Documentation Tour.mp4 146.5 MB
07 Artificial Neural Network and TensorFlow Basics/027 Tensorboard.mp4 144.2 MB
07 Artificial Neural Network and TensorFlow Basics/020 Keras Project Solution - Exploratoy Data Analysis.mp4 143.7 MB
10 Open AI Gym Overview/005 OpenAI Gym - Working with the Environment.mp4 137.5 MB
07 Artificial Neural Network and TensorFlow Basics/012 Keras Regression - Exploratory Data Analysis.mp4 137.0 MB
07 Artificial Neural Network and TensorFlow Basics/023 Keras Project Solutions - Categorical Data.mp4 125.0 MB
04 Matplotlib and Visualization Overview/011 Matplotlib Exercise Questions - Solutions.mp4 123.2 MB
10 Open AI Gym Overview/006 OpenAI Gym - Agent Interacting with the Environment.mp4 116.4 MB
06 Pandas and Scikit-Learn Crash Course/004 Pandas - DataFrames - Part One.mp4 114.4 MB
07 Artificial Neural Network and TensorFlow Basics/017 Keras Classification - Overfitting and Evaluation.mp4 111.2 MB
03 Numpy Basics Overview/002 NumPy Arrays.mp4 109.6 MB
11 Classical Q Learning/017 Continuous Q-Learning - Part Six - Training and Usage.mp4 108.8 MB
11 Classical Q Learning/010 Q-Learning Implementation - Part Four - Agent Training.mp4 107.0 MB
12 Deep Q-Learning/011 DQN Manual Implementation - Part Four - Model Training.mp4 106.9 MB
08 Convolutional Neural Networks with TensorFlow/007 CNN on MNIST - Creating and Training the Model.mp4 98.9 MB
02 Course Set-Up and Installation Procedures/001 Anaconda and Jupyter Notebook Install and Setup.mp4 98.8 MB
07 Artificial Neural Network and TensorFlow Basics/021 Keras Project Solutions - Missing Data - Part One.mp4 96.8 MB
06 Pandas and Scikit-Learn Crash Course/007 Pandas - DataFrames - Part Four.mp4 96.7 MB
04 Matplotlib and Visualization Overview/006 Matplotlib - Subplots Functionality.mp4 96.2 MB
12 Deep Q-Learning/006 DQN Theory and Intuition - Part Four - Experience Replay.mp4 96.0 MB
11 Classical Q Learning/009 Q-Learning Implementation - Part Three - Update Functions.mp4 92.9 MB
08 Convolutional Neural Networks with TensorFlow/014 CNN on Real Image Files - Creating the Model.mp4 90.5 MB
06 Pandas and Scikit-Learn Crash Course/006 Pandas - DataFrames - Part Three.mp4 89.5 MB
12 Deep Q-Learning/005 DQN Theory and Intuition - Part Three - Feedback and Function Approximation.mp4 88.3 MB
11 Classical Q Learning/007 Q-Learning Implementation - Part One - Environment Setup.mp4 88.2 MB
08 Convolutional Neural Networks with TensorFlow/013 CNN on Real Image Files - Data Generation.mp4 87.7 MB
11 Classical Q Learning/015 Continuous Q-Learning - Part Four - Discretization Implementation.mp4 86.2 MB
11 Classical Q Learning/013 Continuous Q-Learning Theory - Part Two- Q-Table Shape.mp4 85.7 MB
07 Artificial Neural Network and TensorFlow Basics/022 Keras Project Solutions - Dealing with Missing Data - Part Two.mp4 85.4 MB
12 Deep Q-Learning/010 DQN Manual Implementation - Part Three - Hyperparameters and Functions.mp4 84.7 MB
07 Artificial Neural Network and TensorFlow Basics/010 Keras Syntax - Creating and Training the Model.mp4 84.3 MB
12 Deep Q-Learning/015 DQN - Keras-RL2 - Part Four - DQN Agent.mp4 84.1 MB
12 Deep Q-Learning/007 DQN Theory and Intuition - Part Five - Mapping Key Ideas to Code.mp4 81.5 MB
04 Matplotlib and Visualization Overview/008 Matplotlib Styling - Colors and Styles.mp4 81.2 MB
07 Artificial Neural Network and TensorFlow Basics/019 Keras Project Notebook Exercise Overview.mp4 80.6 MB
08 Convolutional Neural Networks with TensorFlow/012 CNN on Real Image Files - Reading in the Data.mp4 80.4 MB
11 Classical Q Learning/003 Q-Learning Theory - Part One - Table Intuition.mp4 77.5 MB
06 Pandas and Scikit-Learn Crash Course/009 Scikit-Learn - Using Metrics.mp4 77.3 MB
07 Artificial Neural Network and TensorFlow Basics/013 Keras Regression - EDA Continued.mp4 76.3 MB
07 Artificial Neural Network and TensorFlow Basics/006 Cost Functions and Gradient Descent.mp4 76.0 MB
08 Convolutional Neural Networks with TensorFlow/002 Image Filters and Kernels.mp4 72.3 MB
05 Machine Learning, Deep Learning, and Reinforcement Learning/002 Supervised Machine Learning Process.mp4 71.7 MB
02 Course Set-Up and Installation Procedures/003 Environment Setup Walkthrough.mp4 71.2 MB
10 Open AI Gym Overview/002 OpenAI Overview and History.mp4 69.7 MB
07 Artificial Neural Network and TensorFlow Basics/015 Keras Regression - Model Evaluation and Predictions.mp4 68.9 MB
11 Classical Q Learning/018 Q-Learning Exercise Project.mp4 66.3 MB
07 Artificial Neural Network and TensorFlow Basics/011 Keras Syntax - Model Evaluation.mp4 64.8 MB
08 Convolutional Neural Networks with TensorFlow/009 CNN on CIFAR-10 - The Data.mp4 64.3 MB
07 Artificial Neural Network and TensorFlow Basics/026 Keras Project Solutions - Model Evaluation.mp4 63.2 MB
12 Deep Q-Learning/017 DQN - Exercise Solutions.mp4 62.5 MB
07 Artificial Neural Network and TensorFlow Basics/004 Activation Functions.mp4 62.5 MB
09 Reinforcement Learning - Core Concepts/002 Agents, Environments, and Policy.mp4 62.3 MB
06 Pandas and Scikit-Learn Crash Course/008 Scikit-Learn - Using Train-Test-Split.mp4 60.5 MB
08 Convolutional Neural Networks with TensorFlow/006 CNN on MNIST - The Data.mp4 59.8 MB
04 Matplotlib and Visualization Overview/004 Matplotlib - Implementing Figures and Axes.mp4 59.0 MB
11 Classical Q Learning/006 Q-Learning Theory - Part Four - Programmatic Q Updates.mp4 58.2 MB
08 Convolutional Neural Networks with TensorFlow/003 Convolutional Layers.mp4 58.0 MB
07 Artificial Neural Network and TensorFlow Basics/007 Backpropagation.mp4 57.9 MB
09 Reinforcement Learning - Core Concepts/003 Rewards, Discount Factors, and Bellman Equation.mp4 56.7 MB
11 Classical Q Learning/011 Q-Learning Implementation - Part Five - Visualization and Utilization.mp4 56.6 MB
07 Artificial Neural Network and TensorFlow Basics/016 Keras Classification - EDA and Preprocessing.mp4 56.2 MB
08 Convolutional Neural Networks with TensorFlow/017 CNN Exercise Project Solutions.mp4 55.9 MB
01 Course Overview/002 COURSE_NOTEBOOKS.zip 55.3 MB
02 Course Set-Up and Installation Procedures/004 COURSE_NOTEBOOKS.zip 55.3 MB
05 Machine Learning, Deep Learning, and Reinforcement Learning/001 What is Machine Learning, Deep Learning, and Artificial Intelligence_.mp4 54.6 MB
11 Classical Q Learning/012 Continuous Q-Learning Theory - Part One - Environment Setup.mp4 54.4 MB
11 Classical Q Learning/004 Q-Learning Theory - Part Two - Q Target Equation.mp4 54.3 MB
06 Pandas and Scikit-Learn Crash Course/005 Pandas - DataFrames - Part Two.mp4 54.0 MB
12 Deep Q-Learning/012 DQN - Keras-RL2 - Part One - Overview.mp4 53.7 MB
04 Matplotlib and Visualization Overview/002 Matplotlib Basics.mp4 53.6 MB
04 Matplotlib and Visualization Overview/010 Matplotlib Exercise Questions Overview.mp4 50.7 MB
07 Artificial Neural Network and TensorFlow Basics/009 Keras Syntax - Preparing the Data.mp4 50.3 MB
03 Numpy Basics Overview/004 Numpy Operations - Part Two.mp4 48.6 MB
03 Numpy Basics Overview/006 Numpy Exercise Solutions.mp4 48.6 MB
07 Artificial Neural Network and TensorFlow Basics/002 Perceptron Model.mp4 48.0 MB
07 Artificial Neural Network and TensorFlow Basics/014 Keras Regression - Data Preprocessing and Model Creation.mp4 47.0 MB
08 Convolutional Neural Networks with TensorFlow/015 CNN on Real Image Files - Model Evaluation.mp4 47.0 MB
12 Deep Q-Learning/004 DQN Theory and Intuition - Part Two - Neural Networks for RL.mp4 46.5 MB
03 Numpy Basics Overview/003 Numpy Operations - Part One.mp4 46.4 MB
07 Artificial Neural Network and TensorFlow Basics/005 Multi-Class Classification Considerations.mp4 46.1 MB
06 Pandas and Scikit-Learn Crash Course/003 Pandas - Series Part Two.mp4 45.5 MB
11 Classical Q Learning/016 Continuous Q-Learning - Part Five - Functions and Hyperparameters.mp4 45.4 MB
08 Convolutional Neural Networks with TensorFlow/010 CNN on CIFAR-10 - Evaluating the Model.mp4 45.4 MB
01 Course Overview/002 Course Curriculum Overview.mp4 44.0 MB
11 Classical Q Learning/008 Q-Learning Implementation - Part Two - Table and Hyperparameters.mp4 43.1 MB
01 Course Overview/003 Course Success and Overview.mp4 42.1 MB
04 Matplotlib and Visualization Overview/009 Advanced Matplotlib Commands (Optional).mp4 40.5 MB
06 Pandas and Scikit-Learn Crash Course/002 Pandas - Series Part One.mp4 38.7 MB
08 Convolutional Neural Networks with TensorFlow/008 CNN on MNIST - Model Evaluation.mp4 38.5 MB
11 Classical Q Learning/005 Q-Learning Theory - Part Three - Q-Update Equation.mp4 37.5 MB
10 Open AI Gym Overview/004 OpenAI Gym - Environment Key Ideas.mp4 37.3 MB
07 Artificial Neural Network and TensorFlow Basics/003 Neural Networks.mp4 35.9 MB
04 Matplotlib and Visualization Overview/007 Matplotlib Styling - Legends.mp4 34.1 MB
12 Deep Q-Learning/009 DQN Manual Implementation - Part Two - Artificial Neural Network.mp4 31.9 MB
07 Artificial Neural Network and TensorFlow Basics/025 Keras Project Solutions- Creating and Training the Model.mp4 29.8 MB
12 Deep Q-Learning/002 History of DQN.mp4 28.8 MB
12 Deep Q-Learning/016 DQN - Exercise Overview.mp4 28.3 MB
08 Convolutional Neural Networks with TensorFlow/011 Downloading Data Set for Real Image Lectures.mp4 28.1 MB
08 Convolutional Neural Networks with TensorFlow/004 Pooling Layers.mp4 27.6 MB
09 Reinforcement Learning - Core Concepts/004 Deterministic vs. Stochastic Processes.mp4 27.3 MB
11 Classical Q Learning/002 History of Q-Learning.mp4 27.1 MB
12 Deep Q-Learning/014 DQN - Keras-RL2 - Part Three - Creating the ANN.mp4 26.0 MB
04 Matplotlib and Visualization Overview/003 Matplotlib - Understanding the Figure Object.mp4 25.8 MB
08 Convolutional Neural Networks with TensorFlow/005 MNIST Data Set Overview.mp4 24.7 MB
11 Classical Q Learning/014 Continuous Q-Learning Theory - Part Three - Discretization Theory.mp4 24.7 MB
07 Artificial Neural Network and TensorFlow Basics/024 Keras Project Solutions - Data Preprocessing.mp4 24.0 MB
12 Deep Q-Learning/003 DQN Theory and Intuition - Part One - Review of Core RL Ideas.mp4 23.9 MB
04 Matplotlib and Visualization Overview/005 Matplotlib - Figure Parameters.mp4 23.8 MB
11 Classical Q Learning/001 Introduction to Classical Q-Learning Overview.mp4 22.6 MB
04 Matplotlib and Visualization Overview/001 Introduction to Matplotlib.mp4 21.6 MB
12 Deep Q-Learning/008 DQN Manual Implementation - Part One - Imports and Environment.mp4 20.8 MB
08 Convolutional Neural Networks with TensorFlow/016 CNN Exercise Project Overview.mp4 17.8 MB
12 Deep Q-Learning/013 DQN - Keras-RL2 - Part Two - Imports and Environment.mp4 14.0 MB
03 Numpy Basics Overview/005 Numpy Exercise Overview.mp4 11.5 MB
03 Numpy Basics Overview/001 Introduction to Numpy Section.mp4 11.3 MB
09 Reinforcement Learning - Core Concepts/001 Overview of Core Concepts for Reinforcement Learning Section.mp4 10.7 MB
07 Artificial Neural Network and TensorFlow Basics/008 TensorFlow vs. Keras Explained.mp4 10.4 MB
12 Deep Q-Learning/001 DQN Section Overview.mp4 10.1 MB
07 Artificial Neural Network and TensorFlow Basics/001 Introduction to Artificial Neural Networks.mp4 9.7 MB
07 Artificial Neural Network and TensorFlow Basics/018 Keras Classification - Overview of Project Options.mp4 7.9 MB
08 Convolutional Neural Networks with TensorFlow/001 Convolutional Neural Networks Section Overview.mp4 7.5 MB
10 Open AI Gym Overview/001 Introduction to OpenAI Gym Section.mp4 6.1 MB
12 Deep Q-Learning/110 DQNNaturePaper.pdf 4.4 MB
10 Open AI Gym Overview/005 OpenAI Gym - Working with the Environment.en.srt 43.5 KB
11 Classical Q Learning/019 Q-Learning Exercise Project - Solutions.en.srt 33.5 KB
03 Numpy Basics Overview/002 NumPy Arrays.en.srt 33.1 KB
10 Open AI Gym Overview/006 OpenAI Gym - Agent Interacting with the Environment.en.srt 32.0 KB
11 Classical Q Learning/017 Continuous Q-Learning - Part Six - Training and Usage.en.srt 31.7 KB
12 Deep Q-Learning/005 DQN Theory and Intuition - Part Three - Feedback and Function Approximation.en.srt 31.4 KB
07 Artificial Neural Network and TensorFlow Basics/027 Tensorboard.en.srt 30.7 KB
06 Pandas and Scikit-Learn Crash Course/004 Pandas - DataFrames - Part One.en.srt 30.1 KB
07 Artificial Neural Network and TensorFlow Basics/020 Keras Project Solution - Exploratoy Data Analysis.en.srt 30.0 KB
12 Deep Q-Learning/006 DQN Theory and Intuition - Part Four - Experience Replay.en.srt 29.8 KB
04 Matplotlib and Visualization Overview/006 Matplotlib - Subplots Functionality.en.srt 29.7 KB
07 Artificial Neural Network and TensorFlow Basics/006 Cost Functions and Gradient Descent.en.srt 28.7 KB
07 Artificial Neural Network and TensorFlow Basics/012 Keras Regression - Exploratory Data Analysis.en.srt 28.0 KB
12 Deep Q-Learning/010 DQN Manual Implementation - Part Three - Hyperparameters and Functions.en.srt 27.8 KB
07 Artificial Neural Network and TensorFlow Basics/023 Keras Project Solutions - Categorical Data.en.srt 27.2 KB
11 Classical Q Learning/015 Continuous Q-Learning - Part Four - Discretization Implementation.en.srt 27.0 KB
11 Classical Q Learning/010 Q-Learning Implementation - Part Four - Agent Training.en.srt 26.8 KB
08 Convolutional Neural Networks with TensorFlow/007 CNN on MNIST - Creating and Training the Model.en.srt 26.0 KB
12 Deep Q-Learning/011 DQN Manual Implementation - Part Four - Model Training.en.srt 25.7 KB
04 Matplotlib and Visualization Overview/011 Matplotlib Exercise Questions - Solutions.en.srt 25.6 KB
11 Classical Q Learning/009 Q-Learning Implementation - Part Three - Update Functions.en.srt 25.6 KB
11 Classical Q Learning/013 Continuous Q-Learning Theory - Part Two- Q-Table Shape.en.srt 25.5 KB
07 Artificial Neural Network and TensorFlow Basics/017 Keras Classification - Overfitting and Evaluation.en.srt 25.3 KB
08 Convolutional Neural Networks with TensorFlow/013 CNN on Real Image Files - Data Generation.en.srt 24.3 KB
11 Classical Q Learning/007 Q-Learning Implementation - Part One - Environment Setup.en.srt 24.1 KB
12 Deep Q-Learning/007 DQN Theory and Intuition - Part Five - Mapping Key Ideas to Code.en.srt 24.0 KB
11 Classical Q Learning/003 Q-Learning Theory - Part One - Table Intuition.en.srt 23.4 KB
10 Open AI Gym Overview/003 OpenAI Gym - Documentation Tour.en.srt 23.2 KB
12 Deep Q-Learning/015 DQN - Keras-RL2 - Part Four - DQN Agent.en.srt 23.1 KB
06 Pandas and Scikit-Learn Crash Course/009 Scikit-Learn - Using Metrics.en.srt 22.5 KB
02 Course Set-Up and Installation Procedures/001 Anaconda and Jupyter Notebook Install and Setup.en.srt 22.3 KB
08 Convolutional Neural Networks with TensorFlow/003 Convolutional Layers.en.srt 22.1 KB
06 Pandas and Scikit-Learn Crash Course/007 Pandas - DataFrames - Part Four.en.srt 21.9 KB
04 Matplotlib and Visualization Overview/008 Matplotlib Styling - Colors and Styles.en.srt 21.8 KB
07 Artificial Neural Network and TensorFlow Basics/007 Backpropagation.en.srt 21.8 KB
07 Artificial Neural Network and TensorFlow Basics/021 Keras Project Solutions - Missing Data - Part One.en.srt 21.8 KB
04 Matplotlib and Visualization Overview/004 Matplotlib - Implementing Figures and Axes.en.srt 21.8 KB
08 Convolutional Neural Networks with TensorFlow/012 CNN on Real Image Files - Reading in the Data.en.srt 21.7 KB
07 Artificial Neural Network and TensorFlow Basics/010 Keras Syntax - Creating and Training the Model.en.srt 21.4 KB
06 Pandas and Scikit-Learn Crash Course/006 Pandas - DataFrames - Part Three.en.srt 21.4 KB
08 Convolutional Neural Networks with TensorFlow/014 CNN on Real Image Files - Creating the Model.en.srt 21.2 KB
11 Classical Q Learning/012 Continuous Q-Learning Theory - Part One - Environment Setup.en.srt 21.0 KB
05 Machine Learning, Deep Learning, and Reinforcement Learning/002 Supervised Machine Learning Process.en.srt 20.4 KB
04 Matplotlib and Visualization Overview/002 Matplotlib Basics.en.srt 20.4 KB
09 Reinforcement Learning - Core Concepts/003 Rewards, Discount Factors, and Bellman Equation.en.srt 20.3 KB
07 Artificial Neural Network and TensorFlow Basics/013 Keras Regression - EDA Continued.en.srt 19.9 KB
08 Convolutional Neural Networks with TensorFlow/006 CNN on MNIST - The Data.en.srt 19.4 KB
09 Reinforcement Learning - Core Concepts/002 Agents, Environments, and Policy.en.srt 18.9 KB
07 Artificial Neural Network and TensorFlow Basics/022 Keras Project Solutions - Dealing with Missing Data - Part Two.en.srt 18.9 KB
08 Convolutional Neural Networks with TensorFlow/002 Image Filters and Kernels.en.srt 18.7 KB
07 Artificial Neural Network and TensorFlow Basics/011 Keras Syntax - Model Evaluation.en.srt 18.6 KB
08 Convolutional Neural Networks with TensorFlow/009 CNN on CIFAR-10 - The Data.en.srt 18.1 KB
06 Pandas and Scikit-Learn Crash Course/008 Scikit-Learn - Using Train-Test-Split.en.srt 18.1 KB
10 Open AI Gym Overview/002 OpenAI Overview and History.en.srt 17.8 KB
07 Artificial Neural Network and TensorFlow Basics/004 Activation Functions.en.srt 17.4 KB
02 Course Set-Up and Installation Procedures/003 Environment Setup Walkthrough.en.srt 17.4 KB
11 Classical Q Learning/008 Q-Learning Implementation - Part Two - Table and Hyperparameters.en.srt 17.3 KB
12 Deep Q-Learning/004 DQN Theory and Intuition - Part Two - Neural Networks for RL.en.srt 17.1 KB
05 Machine Learning, Deep Learning, and Reinforcement Learning/001 What is Machine Learning, Deep Learning, and Artificial Intelligence_.en.srt 17.0 KB
07 Artificial Neural Network and TensorFlow Basics/015 Keras Regression - Model Evaluation and Predictions.en.srt 16.9 KB
03 Numpy Basics Overview/003 Numpy Operations - Part One.en.srt 16.9 KB
07 Artificial Neural Network and TensorFlow Basics/005 Multi-Class Classification Considerations.en.srt 16.8 KB
11 Classical Q Learning/004 Q-Learning Theory - Part Two - Q Target Equation.en.srt 16.8 KB
11 Classical Q Learning/016 Continuous Q-Learning - Part Five - Functions and Hyperparameters.en.srt 16.3 KB
07 Artificial Neural Network and TensorFlow Basics/009 Keras Syntax - Preparing the Data.en.srt 16.2 KB
11 Classical Q Learning/011 Q-Learning Implementation - Part Five - Visualization and Utilization.en.srt 16.0 KB
07 Artificial Neural Network and TensorFlow Basics/002 Perceptron Model.en.srt 16.0 KB
06 Pandas and Scikit-Learn Crash Course/003 Pandas - Series Part Two.en.srt 16.0 KB
01 Course Overview/002 Course Curriculum Overview.en.srt 15.8 KB
12 Deep Q-Learning/017 DQN - Exercise Solutions.en.srt 15.5 KB
11 Classical Q Learning/006 Q-Learning Theory - Part Four - Programmatic Q Updates.en.srt 15.4 KB
07 Artificial Neural Network and TensorFlow Basics/026 Keras Project Solutions - Model Evaluation.en.srt 14.8 KB
06 Pandas and Scikit-Learn Crash Course/002 Pandas - Series Part One.en.srt 13.9 KB
06 Pandas and Scikit-Learn Crash Course/005 Pandas - DataFrames - Part Two.en.srt 13.8 KB
10 Open AI Gym Overview/004 OpenAI Gym - Environment Key Ideas.en.srt 13.5 KB
07 Artificial Neural Network and TensorFlow Basics/019 Keras Project Notebook Exercise Overview.en.srt 13.1 KB
08 Convolutional Neural Networks with TensorFlow/015 CNN on Real Image Files - Model Evaluation.en.srt 12.9 KB
08 Convolutional Neural Networks with TensorFlow/017 CNN Exercise Project Solutions.en.srt 12.8 KB
07 Artificial Neural Network and TensorFlow Basics/014 Keras Regression - Data Preprocessing and Model Creation.en.srt 12.7 KB
03 Numpy Basics Overview/004 Numpy Operations - Part Two.en.srt 12.5 KB
11 Classical Q Learning/018 Q-Learning Exercise Project.en.srt 12.5 KB
07 Artificial Neural Network and TensorFlow Basics/016 Keras Classification - EDA and Preprocessing.en.srt 12.2 KB
01 Course Overview/003 Course Success and Overview.en.srt 12.0 KB
04 Matplotlib and Visualization Overview/003 Matplotlib - Understanding the Figure Object.en.srt 12.0 KB
12 Deep Q-Learning/012 DQN - Keras-RL2 - Part One - Overview.en.srt 11.8 KB
11 Classical Q Learning/005 Q-Learning Theory - Part Three - Q-Update Equation.en.srt 11.7 KB
07 Artificial Neural Network and TensorFlow Basics/003 Neural Networks.en.srt 11.6 KB
12 Deep Q-Learning/009 DQN Manual Implementation - Part Two - Artificial Neural Network.en.srt 11.5 KB
08 Convolutional Neural Networks with TensorFlow/010 CNN on CIFAR-10 - Evaluating the Model.en.srt 11.3 KB
03 Numpy Basics Overview/006 Numpy Exercise Solutions.en.srt 11.3 KB
08 Convolutional Neural Networks with TensorFlow/004 Pooling Layers.en.srt 11.0 KB
04 Matplotlib and Visualization Overview/007 Matplotlib Styling - Legends.en.srt 10.7 KB
08 Convolutional Neural Networks with TensorFlow/008 CNN on MNIST - Model Evaluation.en.srt 10.1 KB
04 Matplotlib and Visualization Overview/010 Matplotlib Exercise Questions Overview.en.srt 9.7 KB
08 Convolutional Neural Networks with TensorFlow/011 Downloading Data Set for Real Image Lectures.en.srt 9.0 KB
12 Deep Q-Learning/014 DQN - Keras-RL2 - Part Three - Creating the ANN.en.srt 9.0 KB
09 Reinforcement Learning - Core Concepts/004 Deterministic vs. Stochastic Processes.en.srt 8.1 KB
04 Matplotlib and Visualization Overview/005 Matplotlib - Figure Parameters.en.srt 7.9 KB
12 Deep Q-Learning/008 DQN Manual Implementation - Part One - Imports and Environment.en.srt 7.9 KB
11 Classical Q Learning/014 Continuous Q-Learning Theory - Part Three - Discretization Theory.en.srt 7.8 KB
08 Convolutional Neural Networks with TensorFlow/005 MNIST Data Set Overview.en.srt 7.7 KB
12 Deep Q-Learning/003 DQN Theory and Intuition - Part One - Review of Core RL Ideas.en.srt 7.4 KB
04 Matplotlib and Visualization Overview/001 Introduction to Matplotlib.en.srt 6.9 KB
12 Deep Q-Learning/002 History of DQN.en.srt 6.9 KB
04 Matplotlib and Visualization Overview/009 Advanced Matplotlib Commands (Optional).en.srt 6.7 KB
11 Classical Q Learning/001 Introduction to Classical Q-Learning Overview.en.srt 6.4 KB
07 Artificial Neural Network and TensorFlow Basics/025 Keras Project Solutions- Creating and Training the Model.en.srt 6.1 KB
12 Deep Q-Learning/016 DQN - Exercise Overview.en.srt 5.9 KB
11 Classical Q Learning/002 History of Q-Learning.en.srt 5.8 KB
07 Artificial Neural Network and TensorFlow Basics/024 Keras Project Solutions - Data Preprocessing.en.srt 5.5 KB
12 Deep Q-Learning/013 DQN - Keras-RL2 - Part Two - Imports and Environment.en.srt 5.0 KB
06 Pandas and Scikit-Learn Crash Course/033 Advertising.csv 4.1 KB
08 Convolutional Neural Networks with TensorFlow/016 CNN Exercise Project Overview.en.srt 4.0 KB
07 Artificial Neural Network and TensorFlow Basics/001 Introduction to Artificial Neural Networks.en.srt 3.4 KB
07 Artificial Neural Network and TensorFlow Basics/008 TensorFlow vs. Keras Explained.en.srt 3.2 KB
03 Numpy Basics Overview/001 Introduction to Numpy Section.en.srt 3.1 KB
12 Deep Q-Learning/001 DQN Section Overview.en.srt 3.1 KB
09 Reinforcement Learning - Core Concepts/001 Overview of Core Concepts for Reinforcement Learning Section.en.srt 2.8 KB
01 Course Overview/001 Welcome Message.html 2.7 KB
08 Convolutional Neural Networks with TensorFlow/001 Convolutional Neural Networks Section Overview.en.srt 2.7 KB
07 Artificial Neural Network and TensorFlow Basics/018 Keras Classification - Overview of Project Options.en.srt 2.6 KB
03 Numpy Basics Overview/005 Numpy Exercise Overview.en.srt 2.1 KB
10 Open AI Gym Overview/001 Introduction to OpenAI Gym Section.en.srt 1.6 KB
02 Course Set-Up and Installation Procedures/002 Note on Environment Setup.html 1.6 KB
06 Pandas and Scikit-Learn Crash Course/001 Pandas and Scikit-Learn Overview.html 1.1 KB
09 Reinforcement Learning - Core Concepts/005 Tabular Reinforcement Learning.html 1.1 KB
08 Convolutional Neural Networks with TensorFlow/external-assets-links.txt 180 bytes

[Udemy] Practical AI with Python and Reinforcement Learning (07.2021)

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