NEW LIST 2023 - 2024: Machine-Learning / Deep-Learning / AI + Web3 -Tutorials
Hi - Thanks for dropping by!
I will be updating this tutorials site on a daily basis adding all relevant topcis for 2022 - 2024 especially pertaining to GPU programming, Data Centric AI, Emerging topics like Sustainable AI with Web3AI.js (DeFI, DAO, NFT) and much more.
NOTE: All these tutorials are supported and accelerated on NVIDIA GPUs
More importantly the applications of ML/DL/AI into industry areas such as Transportation, Medicine/Healthcare etc. will be something I'll watch with keen interest and would love to share the same with you.
Finally, it is YOUR help I will seek to make it more useful and less boring, so please do suggest/comment/contribute!
Index
- deep-learning
- scikit-learn
- statistical-inference-scipy
- pandas
- matplotlib
- numpy
- python-data
- kaggle-and-business-analyses
- spark
- mapreduce-python
- amazon web services
- command lines
- misc
- notebook-installation
- Curated list of Deep Learning / AI blogs
- credits
- contributing
- contact-info
- license
deep-learning
IPython Notebook(s) and other programming tools such as Torch/Lua/D lang in demonstrating deep learning functionality.
uber-pyro-probabalistic-tutorials
Additional PyRo tutorials:
- pyro-examples/full examples
- pyro-examples/Variational Autoencoders
- pyro-examples/Bayesian Regression
- pyro-examples/Deep Markov Model
- pyro-examples/AIR(Attend Infer Repeat)
- pyro-examples/Semi-Supervised VE
- pyro-examples/GMM
- pyro-examples/Gaussian Process
- pyro-examples/Bayesian Optimization
- Full Pyro Code
netflix-vectorflow-tutorials
pytorch-tutorials
Level | Description |
---|---|
Beginners/Zakizhou | Learning the basics of PyTorch from Facebook. |
Intermedia/Quanvuong | Learning the intermediate stuff about PyTorch of from Facebook. |
Advanced/Chsasank | Learning the advanced stuff about PyTorch of from Facebook. |
Learning PyTorch by Examples - Numpy, Tensors and Autograd | At its core, PyTorch provides two main features an n-dimensional Tensor, similar to numpy but can run on GPUs AND automatic differentiation for building and training neural networks. |
PyTorch - Getting to know autograd.Variable, Gradient, Neural Network | Here we start with ultimate basics of Tensors, wrap a Tensor with Variable module, play with nn.Module and implement forward and backward function. |
tensor-flow-tutorials
Additional TensorFlow tutorials:
- pkmital/tensorflow_tutorials
- nlintz/TensorFlow-Tutorials
- alrojo/tensorflow-tutorial
- BinRoot/TensorFlow-Book
Notebook | Description |
---|---|
tsf-basics | Learn basic operations in TensorFlow, a library for various kinds of perceptual and language understanding tasks from Google. |
tsf-linear | Implement linear regression in TensorFlow. |
tsf-logistic | Implement logistic regression in TensorFlow. |
tsf-nn | Implement nearest neighboars in TensorFlow. |
tsf-alex | Implement AlexNet in TensorFlow. |
tsf-cnn | Implement convolutional neural networks in TensorFlow. |
tsf-mlp | Implement multilayer perceptrons in TensorFlow. |
tsf-rnn | Implement recurrent neural networks in TensorFlow. |
tsf-gpu | Learn about basic multi-GPU computation in TensorFlow. |
tsf-gviz | Learn about graph visualization in TensorFlow. |
tsf-lviz | Learn about loss visualization in TensorFlow. |
tensor-flow-exercises
Notebook | Description |
---|---|
tsf-not-mnist | Learn simple data curation by creating a pickle with formatted datasets for training, development and testing in TensorFlow. |
tsf-fully-connected | Progressively train deeper and more accurate models using logistic regression and neural networks in TensorFlow. |
tsf-regularization | Explore regularization techniques by training fully connected networks to classify notMNIST characters in TensorFlow. |
tsf-convolutions | Create convolutional neural networks in TensorFlow. |
tsf-word2vec | Train a skip-gram model over Text8 data in TensorFlow. |
tsf-lstm | Train a LSTM character model over Text8 data in TensorFlow. |
theano-tutorials
Notebook | Description |
---|---|
theano-intro | Intro to Theano, which allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation. |
theano-scan | Learn scans, a mechanism to perform loops in a Theano graph. |
theano-logistic | Implement logistic regression in Theano. |
theano-rnn | Implement recurrent neural networks in Theano. |
theano-mlp | Implement multilayer perceptrons in Theano. |
keras-tutorials
Notebook | Description |
---|---|
keras | Keras is an open source neural network library written in Python. It is capable of running on top of either Tensorflow or Theano. |
setup | Learn about the tutorial goals and how to set up your Keras environment. |
intro-deep-learning-ann | Get an intro to deep learning with Keras and Artificial Neural Networks (ANN). |
Perceptrons and Adaline | Implement Peceptron and adaptive linear neurons. |
MLP and MNIST Data | Classifying handwritten digits,implement MLP, train and debug ANN |
theano | Learn about Theano by working with weights matrices and gradients. |
keras-otto | Learn about Keras by looking at the Kaggle Otto challenge. |
ann-mnist | Review a simple implementation of ANN for MNIST using Keras. |
conv-nets | Learn about Convolutional Neural Networks (CNNs) with Keras. |
conv-net-1 | Recognize handwritten digits from MNIST using Keras - Part 1. |
conv-net-2 | Recognize handwritten digits from MNIST using Keras - Part 2. |
keras-models | Use pre-trained models such as VGG16, VGG19, ResNet50, and Inception v3 with Keras. |
auto-encoders | Learn about Autoencoders with Keras. |
rnn-lstm | Learn about Recurrent Neural Networks (RNNs) with Keras. |
lstm-sentence-gen | Learn about |