Deep Learning Book Chinese Translation
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
The most cited deep learning papers
DeepFaceLab is the leading software for creating deepfakes.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
The best design tools and plugins for everything
Books for machine learning, deep learning, math, NLP, CV, RL, etc
Python notebooks with ML and deep learning examples with Azure Machine Learning | Microsoft
AKG (Auto Kernel Generator) is an optimizer for operators in Deep Learning Networks, which provides the ability to automatically fuse ops with specific patterns.
Human activity recognition, or HAR, is a challenging time series classification task. It involves predicting the movement of a person based on sensor data and traditionally involves deep domain expertise and methods from signal processing to correctly engineer features from the raw data in order to fit a machine learning model.
DeepFaceLab is the leading software for creating deepfakes.
Deep Learning Examples
A Deep-Learning Chess Engine with some awesome features
Machine Learning and Deep Learning lessons.
Natural language processing (NLP) is an exciting branch of artificial intelligence (AI) that allows machines to break down and understand human language. I plan to walk through text pre-processing techniques, machine learning techniques and Python libraries for NLP. Text pre-processing techniques include tokenization, text normalization and data cleaning. Once in a standard format, various machine learning techniques can be applied to better understand the data. This includes using popular modeling techniques to classify emails as spam or not, or to score the sentiment of a tweet on Twitter. Newer, more complex techniques can also be used such as topic modeling, word embeddings or text generation with deep learning. We will walk through an example in Jupyter Notebook that goes through all of the steps of a text analysis project, using several NLP libraries in Python including NLTK, TextBlob, spaCy and gensim along with the standard machine learning libraries including pandas and scikit-learn.
Developed using Pybullet, OpenCV and Deep Learning
This project contains codes for solving complex problems with Spark. It also shows extension of new libraries and API with Spark such as Deep Learning with Spark, Geo-spatial analytics with Spark etc
Repository dedicated to Deep Learning Course took at the Federal University of Paraíba, Brazil
Introduction to Deep Reinforcement Learning
Survey on the diversity problem in deep learning dialogue systems
An efficient video loader for deep learning with smart shuffling that's super easy to digest
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
An efficient video loader for deep learning with smart shuffling that's super easy to digest
Resources for deep learning with satellite & aerial imagery
Create Neural Networks in a simple, clutter less manner.
HPC System and Software Testing Framework
Deep Learning (with PyTorch)
links to conference publications in graph-based deep learning
Picker is a cross-platform UI component for selecting an item from a list of options.
Deep Learning based cell composition analysis with Scaden.
OneFlow is a performance-centered and open-source deep learning framework.
Repository on the collaborative IVADO medical imaging project between the Mila and NeuroPoly labs.
Powerful and efficient Computer Vision Annotation Tool (CVAT)
... I send out a list of most interesting libraries and apps in the "Deep Learning" section to about 1100 subscribers.
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