Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

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Efficient Segmentation Networks

Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)

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Tez

Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch.

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Awesome Bert Nlp

A curated list of NLP resources focused on BERT, attention mechanism, Transformer networks, and transfer learning.

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Flashtorch

Visualization toolkit for neural networks in PyTorch! Demo -->

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Keras Rl

Deep Reinforcement Learning for Keras.

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Tensorflow Value Iteration Networks

TensorFlow implementation of the Value Iteration Networks (NIPS '16) paper

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Layer

Neural network inference the Unix way

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Graph nets

Build Graph Nets in Tensorflow

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Keras Js

Run Keras models in the browser, with GPU support using WebGL

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Sense

Enhance your application with the ability to see and interact with humans using any RGB camera.

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Speech Denoising Wavenet

A neural network for end-to-end speech denoising

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Machine Learning Articles

Monthly Series - Top 10 Machine Learning Articles

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Dissecting Reinforcement Learning

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

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Edward

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

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Geomstats

Computations and statistics on manifolds with geometric structures.

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Chemprop

Message Passing Neural Networks for Molecule Property Prediction

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Ofxdarknet

darknet neural network addon for openFrameworks

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Learn Data Science For Free

This repositary is a combination of different resources lying scattered all over the internet. The reason for making such an repositary is to combine all the valuable resources in a sequential manner, so that it helps every beginners who are in a search of free and structured learning resource for Data Science. For Constant Updates Follow me in …

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Deep Learning Specialization Coursera

Deep Learning Specialization by Andrew Ng on Coursera.

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Bayesian Analysis Recipes

A collection of Bayesian data analysis recipes using PyMC3

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Diffeqflux.jl

Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

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Introtodeeplearning

Lab Materials for MIT 6.S191: Introduction to Deep Learning

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Augmentor

Image augmentation library in Python for machine learning.

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Deeplearning.ai Natural Language Processing Specialization

This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai

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Beholder

A TensorBoard plugin for visualizing arbitrary tensors in a video as your network trains.

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Seq2seqchatbots

A wrapper around tensor2tensor to flexibly train, interact, and generate data for neural chatbots.

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Onnxruntime

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator