1906 Open source projects that are alternatives of or similar to Trending Deep Learning

Top 200 deep learning Github repositories sorted by the number of stars.

This is an open sourced book on deep learning.

Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification

deeplearning.ai , By Andrew Ng, All video link

A collection of computer vision projects for Acute Lymphoblastic Leukemia classification/early detection.

Traffic Sign Detection. Code for the paper entitled "Evaluation of deep neural networks for traffic sign detection systems".

TensorFlow and Deep Learning Tutorials

🚀 FREE AI Resources - 🎓 Courses, 👷 Jobs, 📝 Blogs, 🔬 AI Research, and many more - for everyone!

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

MIVisionX toolkit is a comprehensive computer vision and machine intelligence libraries, utilities and applications bundled into a single toolkit.

Human Activity Recognition (HAR) with 1D Convolutional Neural Network in Python and Keras

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Deep learning codes and projects using Python

Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)

PyTorch tutorial for learners

Machine Reading Comprehension in Tensorflow

Komputation is a neural network framework for the Java Virtual Machine written in Kotlin and CUDA C.

Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

A Neural Networking library based on NumPy only

The Official Deep Learning Framework for Route-based Place Recognition

Deep Reinforcement Learning based Trading Agent for Bitcoin

HDLTex: Hierarchical Deep Learning for Text Classification

深度学习与PyTorch入门实战视频教程 配套源代码和PPT

RMDL: Random Multimodel Deep Learning for Classification

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

The Cutest Deep Learning Framework which is also a wonderful Declarative Language

An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classification

A binary release of trained deep reinforcement learning models trained in the Atari machine learning benchmark, and a software release that enables easy visualization and analysis of models, and comparison across training algorithms.

This is a tutorial for PyTorch Geometric on the YooChoose dataset

A tensorflow implementation with SSD model for person detection and Kalman Filtering combined for tracking

Transfer Learning Suite in Keras. Perform transfer learning using any built-in Keras image classification model easily!

A Knowledge Base for the FB Group Artificial Intelligence and Deep Learning (AIDL)

Deep Learning Autonomous Car based on Raspberry Pi, SunFounder PiCar-V Kit, TensorFlow, and Google's EdgeTPU Co-Processor

Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell, buy, or hold the stocks to maximize the gain in asset value. The paper also acknowledges the need for a system that predicts the trend in stock value to work along with the reinforcement …

Reinforcement Learning and Decision Making tutorials explained at an intuitive level and with Jupyter Notebooks

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

VIP cheatsheets for Stanford's CS 230 Deep Learning

Simple (but often Strong) Baselines for POMDPs in PyTorch - ICML 2022

If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!

Python script for illustrating Convolutional Neural Networks (CNN) using Keras-like model definitions

My bachelor's thesis—analyzing the application of LSTM-based RNNs on financial markets. 🤓

Codes and Templates from the SuperDataScience Course

Moore Machine Networks (MMN): Learning Finite-State Representations of Recurrent Policy Networks

Named Entity Recognition using multilayered bidirectional LSTM

Applying Machine Learning and AI Algorithms applied to Trading for better performance and low Std.

Code base for solving Markov Decision Processes and Reinforcement Learning problems using Recurrent Convolutional Neural Networks.

Train robotic agents to learn to plan pushing and grasping actions for manipulation with deep reinforcement learning.

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

State of the Art Neural Networks for Deep Learning

Deep Learning using Rectified Linear Units (ReLU)

A curated list of awesome awesomeness about artificial intelligence

RAD: Reinforcement Learning with Augmented Data

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

A generic image detection program that uses Google's Machine Learning library, Tensorflow and a pre-trained Deep Learning Convolutional Neural Network model called Inception.

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

Deep Learning Computer Vision Algorithms for Real-World Use

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