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BootCamps Notes 👢🏕🎶

The structure of this directory is as follow:

  1. Numpy 🕸️
    >>>0. NumPy-Arrays
    >>>1. NumPy-Indexing-and-Selection
    >>>2. NumPy-Operations
    >>>3. NumPy-Exercises
    >>>4. NumPy-Exercises-Solutions

  2. Pandas 🐼
    >>>0. Intro-to-Pandas
    >>>1. Series
    >>>2. DataFrames
    >>>3. Missing-Data
    >>>4. Groupby
    >>>5. Operations
    >>>6. Data-Input-and-Output
    >>>7. Pandas-Exercises
    >>>8. Pandas-Exercises-Solutions

  3. Pytorch Basics 🥀
    >>>0. Tensor-Basics
    >>>1. Tensor-Operations
    >>>2. PyTorch-Basics-Exercises
    >>>3. PyTorch-Basics-Exercises-Solutions

  4. Pytorch for Deeplearning Bootcamp: 🌟

    a. ANN - Artificial Neural Networks
    >>>0. PyTorch-Gradients
    >>>1. Linear-Regression-with-PyTorch
    >>>2. DataSets-with-Pytorch
    >>>3. Basic-PyTorch-NN
    >>>4. a-Full-ANN-Code-Along-Regression
    >>>5. b-Full-ANN-Code-Along-Classification
    >>>6. Neural-Network-Exercises
    >>>7. Neural-Network-Exercises-Solutions
    >>>8. Recap-Saving-and-Loading-Trained-Models

    b. CNN - Convolutional Neural Networks
    >>>0. MNIST-ANN-Code-Along
    >>>1. MNIST-with-CNN
    >>>2. CIFAR-CNN-Code-Along
    >>>3. Loading-Real-Image-Data
    >>>4. CNN-on-Custom-Images
    >>>5. CNN-Exercises
    >>>6. CNN-Exercises-Solutions

    c. RNN - Recurrent Neural Networks
    >>>0. Basic-RNN
    >>>1. RNN-on-a-Time-Series
    >>>2. RNN-Exercises
    >>>3. RNN-Exercises-Solutions

    d. NLP with PyTorch
    >>>0. RNN-for-Text-Generation
    e. Using GPU
    >>>0. Using-GPU-and-CUDA

  5. Tensorflow BootCamp: 🌊

    a. Colab Basics 🐕
    >>>0 Demo
    >>>1. Installing Tensorflow
    >>>2. Loading Data

    b. Machine Learning Basics 🌽
    >>>1. Linear Classification
    >>>2. Linear Regression

    c. ANN - Artificial Neural Networks🍞
    >>>1. ANN MNIST
    >>>2. ANN Regression

    d. CNN - Convolutional Neural Networks 🍟
    >>>1. Fashion MNIST
    >>>2. CIFAR
    >>>3. Improved CIFAR

    e. RNN - Recurrent Neural Networks ⛈️
    >>>1. Autoregressive Model
    >>>2. Simple RNN sine
    >>>3. RNN Shape
    >>>4. LSTM Non-linear
    >>>5. Long Distance
    >>>6. RNN MNIST
    >>>7. Stock Returns

    f. NLP - Natural Language Processing 🌚
    >>>1. Text Preprocessing
    >>>2. Spam Detection CNN
    >>>3. Spam Detection RNN

    g. Recommendar Systems 🪅
    >>>1. Recommendar System

    h. Transfer Learning 🪭
    >>>1. Transfer Learning
    >>>2. Transfer Learning with Data Augmentation

    i. GANs - Generative Adversarial Networks 🎀
    >>>1. GAN

    j. Advance Tensorflow 🌨️
    >>>1. Tensorflow serving >>>2. Mirror Strategy
    >>>3. TFLite
    >>>4. TPU

    k. Low-Level Tensorflow 🪄
    >>>1. Basic Computation
    >>>2. Variables and Gradients
    >>>3. Build your own Model

soon to be added... 🧦

  1. matplotlib
  2. seaborn
  3. Python for DataSceince and Machine Learning