6682 Open source projects that are alternatives of or similar to Cs231

Udacity Self-Driving Car Engineer Nanodegree. Project: Build a Traffic Sign Recognition Classifier

Keras tutorial for beginners (using TF backend)

Resources for students in the Udacity's Machine Learning Engineer Nanodegree to work through Stanford's Convolutional Neural Networks for Visual Recognition course (CS231n).

TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow

This repository stores the files used for my summer internship's work on "teacher-student learning", an experimental method for training deep neural networks using a trained teacher model.

Deep learning codes and projects using Python

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

This toolbox is support material for the book on CNN (http://www.convolution.network).

Tutoriais de Python, Data Science, Machine Learning e Deep Learning - Sigmoidal

Visualisations for Convolutional Neural Networks in Pytorch

Generating Captions for images using Deep Learning

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

A machine learning experiment

My assignment solutions for CS231n - Convolutional Neural Networks for Visual Recognition

A journey into Convolutional Neural Network visualization

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

A Tensorflow implementation of CapsNet(Capsules Net) apply on german traffic sign dataset

All about attention in neural networks. Soft attention, attention maps, local and global attention and multi-head attention.

A CNN Variational Autoencoder (CNN-VAE) implemented in PyTorch

RadIO is a library for data science research of computed tomography imaging

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

Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

My personal notes, presentations, and notebooks on everything Deep Learning.

A clear, concise, simple yet powerful and efficient API for deep learning.

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

MotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and gyroscope)

Implementations of some popular Saliency Maps in Keras

Amacımız Türkçe NLP literatüründeki birçok farklı sorunu bir arada çözebilen, eşsiz yaklaşımlar öne süren ve literatürdeki çalışmaların eksiklerini gideren open source bir yazım destekleyicisi/denetleyicisi oluşturmak. Kullanıcıların yazdıkları metinlerdeki yazım yanlışlarını derin öğrenme yaklaşımıyla çözüp aynı zamanda metinlerde anlamsal analizi de gerçekleştirerek bu bağlamda ortaya çıkan yanlışları da fark edip düzeltebilmek.

Important paper implementations for Question Answering using PyTorch

🟣 Object detection of abstract shapes with neural networks

Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning

Anomaly detection for temporal data using LSTMs

Semi-Supervised Video Object Segmentation (VOS) with Tensorflow. Includes implementation of *MaskRNN: Instance Level Video Object Segmentation (NIPS 2017)* as part of the NIPS Paper Implementation Challenge.

Automatic image captioning model based on Caffe, using features from bottom-up attention.

Build a CNN network to predict 3D bounding box of car from 2D image.

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

CNN image style transfer 🎨.

Grokking Deep Reinforcement Learning

Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron

TensorFlow Tutorials

Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

an Open Course Platform for Stanford CS224n (2020 Winter)

Applying Data Science and Machine Learning to Solve Real World Business Problems

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

🤖 Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford

CS231n Assignments Solutions - Spring 2020

Machine learning algorithms for many-body quantum systems

These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.

Machine Learning notebooks for refreshing concepts.

Python solutions to the problem sets of Stanford's graduate course on Machine Learning, taught by Prof. Andrew Ng

Place recognition with WiFi fingerprints using Autoencoders and Neural Networks

links to conference publications in graph-based deep learning

Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.

Image Captioning using InceptionV3 and beam search