TensorFlow-Tutorials
Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions
| TensorFlow-Tutorials | Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions | |
|---|---|---|
| 2 | 1 | |
| 9,250 | 1,793 | |
| - | - | |
| 0.0 | 10.0 | |
| over 3 years ago | over 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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TensorFlow-Tutorials
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Probabilistic forecasting
"deep neural network" https://github.com/Hvass-Labs/TensorFlow-Tutorials
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Plagiarism is just bad
The majority of this code is taken from the TensorFlow-Tutorials. I highly recommend them to those who want to get started with TensorFlow.
Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions
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Best Reinforcement Learning course?
You should also consider solving the problems, but here is the solutions in case you are stuck with some problem.
What are some alternatives?
car-damage-detection - Detectron2 for car damage detection using custom dataset
Machine-Learning-Specialization-Coursera - Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
YOLO_Object_Detection - This is the code for "YOLO Object Detection" by Siraj Raval on Youtube
Data_Structures_and_Algorithms_in_Python - :book: Worked Solutions of "Data Structures & Algorithms in Python", written by Michael T. Goodrich, Roberto Tamassia and Michael H. Goldwasser. ✏️
TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Practical_RL - A course in reinforcement learning in the wild
cs231n - Note and Assignments for CS231n: Convolutional Neural Networks for Visual Recognition
m1-machine-learning-test - Code for testing various M1 Chip benchmarks with TensorFlow.
TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0
Deep-Learning-In-Production - Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
TextWorld - TextWorld is a sandbox learning environment for the training and evaluation of reinforcement learning (RL) agents on text-based games.