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‎README.md

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Please head to [www.deeplearningwizard.com](https://www.deeplearningwizard.com/) to start learning! It is mobile/tablet friendly and open-source.
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## Repository Details
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This repository contains all the notebooks and mkdocs markdown files of the tutorials covering machine learning, deep learning, scalable database, programming, data processing and data visualization powering the website.
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This repository contains all the notebooks and mkdocs markdown files of the tutorials covering machine learning, deep learning, deep reinforcement learning, data engineering, general programming, and visualizations powering the website.
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Take note this is an early work in progress, do be patient as we gradually upload our guides.
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## Sections and Subsections
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- [Deep Learning and Deep Reinforcement Learning Tutorials (Libraries: Python, PyTorch, Gym, NumPy, Matplotlib and more)](https://www.deeplearningwizard.com/deep_learning/intro/)
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- Deep Learning and Deep Reinforcement Learning Tutorials (Libraries: Python, PyTorch, Gym, NumPy, Matplotlib and more)
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- [Introduction](https://www.deeplearningwizard.com/deep_learning/intro/)
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- [Course Progression](https://www.deeplearningwizard.com/deep_learning/course_progression/)
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- [Matrices](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_matrices/)
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- [Gradients](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_gradients/)
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- [Linear Regression](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_linear_regression/)
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- [Logistic Regression](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_logistic_regression/)
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- [Feedforward Neural Network (FNN)](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_feedforward_neuralnetwork/)
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- [Convolutional Neural Network (CNN)](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_convolutional_neuralnetwork/)
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- [Recurrent Neural Network (RNN)](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_recurrent_neuralnetwork/)
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- [Long Short-Term Memory Network (LSTM)](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_lstm_neuralnetwork/)
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- [Autoencoders (AE)](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_autoencoder/)
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- [Fully Connected Overcomplete Autoencoders](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_fc_overcomplete_ae/)
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- [Derivative, Gradient and Jacobian](https://www.deeplearningwizard.com/deep_learning/boosting_models_pytorch/derivative_gradient_jacobian/)
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- [Forward- and Backward-propagation and Gradient Descent (From Scratch FNN Regression)](https://www.deeplearningwizard.com/deep_learning/boosting_models_pytorch/forwardpropagation_backpropagation_gradientdescent/)
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- [From Scratch Logistic Regression Classification](https://www.deeplearningwizard.com/deep_learning/fromscratch/fromscratch_logistic_regression/)
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- [From Scratch CNN Classification](https://www.deeplearningwizard.com/deep_learning/fromscratch/fromscratch_cnn/)
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- [Learning Rate Scheduling](https://www.deeplearningwizard.com/deep_learning/boosting_models_pytorch/lr_scheduling/)
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- [Optimization Algorithms](https://www.deeplearningwizard.com/deep_learning/boosting_models_pytorch/optimizers/)
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- [Weight Initialization and Activation Functions](https://www.deeplearningwizard.com/deep_learning/boosting_models_pytorch/weight_initialization_activation_functions/)
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- [Supervised to Reinforcement Learning](https://www.deeplearningwizard.com/deep_learning/deep_reinforcement_learning_pytorch/supervised_to_rl/)
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- [Markov Decision Processes and Bellman Equations](https://www.deeplearningwizard.com/deep_learning/deep_reinforcement_learning_pytorch/bellman_mdp/)
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- [Dynamic Programming](https://www.deeplearningwizard.com/deep_learning/deep_reinforcement_learning_pytorch/dynamic_programming_frozenlake/)
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- [Speed Optimization Basics Numba](https://www.deeplearningwizard.com/deep_learning/production_pytorch/speed_optimization_basics_numba/)
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- [Machine Learning Tutorials (Libraries: Python, cuDF RAPIDS, cuML RAPIDS, pandas, numpy, scikit-learn and more)](https://www.deeplearningwizard.com/machine_learning/intro/)
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- Practical Deep Learning with PyTorch
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- [Matrices](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_matrices/)
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- [Gradients](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_gradients/)
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- [Linear Regression](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_linear_regression/)
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- [Logistic Regression](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_logistic_regression/)
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- [Feedforward Neural Network (FNN)](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_feedforward_neuralnetwork/)
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- [Convolutional Neural Network (CNN)](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_convolutional_neuralnetwork/)
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- [Recurrent Neural Network (RNN)](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_recurrent_neuralnetwork/)
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- [Long Short-Term Memory Network (LSTM)](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_lstm_neuralnetwork/)
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- [Autoencoders (AE)](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_autoencoder/)
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- [Fully Connected Overcomplete Autoencoders](https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_fc_overcomplete_ae/)
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- Improving Deep Learning with PyTorch
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- [Derivative, Gradient and Jacobian](https://www.deeplearningwizard.com/deep_learning/boosting_models_pytorch/derivative_gradient_jacobian/)
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- [Forward- and Backward-propagation and Gradient Descent (From Scratch FNN Regression)](https://www.deeplearningwizard.com/deep_learning/boosting_models_pytorch/forwardpropagation_backpropagation_gradientdescent/)
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- [Learning Rate Scheduling](https://www.deeplearningwizard.com/deep_learning/boosting_models_pytorch/lr_scheduling/)
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- [Optimization Algorithms](https://www.deeplearningwizard.com/deep_learning/boosting_models_pytorch/optimizers/)
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- [Weight Initialization and Activation Functions](https://www.deeplearningwizard.com/deep_learning/boosting_models_pytorch/weight_initialization_activation_functions/)
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- Deep Reinforcement Learning with PyTorch
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- [Supervised to Reinforcement Learning](https://www.deeplearningwizard.com/deep_learning/deep_reinforcement_learning_pytorch/supervised_to_rl/)
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- [Markov Decision Processes and Bellman Equations](https://www.deeplearningwizard.com/deep_learning/deep_reinforcement_learning_pytorch/bellman_mdp/)
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- [Dynamic Programming](https://www.deeplearningwizard.com/deep_learning/deep_reinforcement_learning_pytorch/dynamic_programming_frozenlake/)
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- From Scratch Deep Learning with PyTorch/Python
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- [From Scratch Logistic Regression Classification](https://www.deeplearningwizard.com/deep_learning/fromscratch/fromscratch_logistic_regression/)
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- Compute Optimization
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- [Speed Optimization Basics Numba](https://www.deeplearningwizard.com/deep_learning/production_pytorch/speed_optimization_basics_numba/)
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- Machine Learning Tutorials (Libraries: Python, cuDF RAPIDS, cuML RAPIDS, pandas, numpy, scikit-learn and more)
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- RAPIDS cuDF
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- [Intro](https://www.deeplearningwizard.com/machine_learning/intro/)
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- [GPU DataFrames](https://www.deeplearningwizard.com/machine_learning/gpu/rapids_cudf/)
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- [CPU/GPU Fractional Differencing](https://www.deeplearningwizard.com/machine_learning/gpu/gpu_fractional_differencing/)
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- [Programming Tutorials (Libraries: C++, Python, Bash and more)](https://www.deeplearningwizard.com/programming/intro/)
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- [C++](https://www.deeplearningwizard.com/programming/cpp/cpp/)
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- [Bash](https://www.deeplearningwizard.com/programming/bash/bash/)
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- [Python](https://www.deeplearningwizard.com/programming/python/python/)
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- [Javascript](https://www.deeplearningwizard.com/programming/javascript/javascript/)
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- [Electron](https://www.deeplearningwizard.com/programming/electron/electron/)
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- [Scalable Database Tutorials (Libraries: Apache Cassandra, Bash, Python and more)](https://www.deeplearningwizard.com/database/intro/)
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- [Apache Cassandra Cluster Setup](https://www.deeplearningwizard.com/database/setting_up_cluster/)
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- Programming Tutorials (Libraries: C++, Python, Bash and more)
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- [Intro](https://www.deeplearningwizard.com/programming/intro/)
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- [C++](https://www.deeplearningwizard.com/programming/cpp/cpp/)
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- [Bash](https://www.deeplearningwizard.com/programming/bash/bash/)
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- [Python](https://www.deeplearningwizard.com/programming/python/python/)
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- [Javascript](https://www.deeplearningwizard.com/programming/javascript/javascript/)
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- [Electron](https://www.deeplearningwizard.com/programming/electron/electron/)
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- Data Engineering (Libraries: Bash, Databricks, Delta Live Tables, Parquet, Python, Cassandra, and more)
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- Cassandra (NoSQL)
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- [Introduction](https://www.deeplearningwizard.com/data_engineering/nosql/cassandra/intro/)
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- [Apache Cassandra Cluster Setup](https://www.deeplearningwizard.com/data_engineering/nosql/cassandra/setting_up_cluster/)
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## About Deep Learning Wizard
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We deploy a top-down approach that enables you to grasp deep learning theories and code easily and quickly. We have open-sourced all our materials through our Deep Learning Wizard Wikipedia. For visual learners, feel free to sign up for our video course and join thousands of deep learning wizards.

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