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

Creation Time	July 10, 2024, 6:40 a.m.
Last Access Time	Nov. 16, 2024, 11:36 p.m.
File Size	7.4 GB
Keywords	and 07 AI Reinforcement Udemy Practical Python 2021 Learning with
Total Requests	45
Total Files	251
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

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)

File List

Download Torrent

Related Resources

Copyright Infringement