6332 Open source projects that are alternatives of or similar to Deep Learning Specialization Coursera

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

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

该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。

Machine Learning notebooks for refreshing concepts.

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

Image augmentation library in Python for machine learning.

Anomaly detection for temporal data using LSTMs

Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

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

Plain python implementations of basic machine learning algorithms

（完结）网易云课堂微专业《深度学习工程师》听课笔记，编程作业和课后练习

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

This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera

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

🟣 Object detection of abstract shapes with neural networks

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

Deep learning codes and projects using Python

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.

This is Andrew NG Coursera Handwritten Notes.

pytorch 包教不包会

AI for everyone! 🎉 Neural networks, tools and a library we use in Supervisely

Grokking Deep Reinforcement Learning

Repo for the Deep Reinforcement Learning Nanodegree program

A simple probabilistic programming language.

🛠 All-in-one web-based IDE specialized for machine learning and data science.

Deep Learning Specialization courses by Andrew Ng, deeplearning.ai

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.

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

Machine Learning and Reinforcement Learning in Finance New York University Tandon School of Engineering

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

Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.

quizzes/assignments for mathematics for machine learning specialization on coursera

A collection of Bayesian data analysis recipes using PyMC3

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

吴恩达机器学习coursera课程，学习代码(2017年秋) The Stanford Coursera course on MachineLearning with Andrew Ng

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

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

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

PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.

Codes for weekly challenges on Deep Learning by Siraj

links to conference publications in graph-based deep learning

Machine Learning Practical course repository

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.

Probabilistic reasoning and statistical analysis in TensorFlow

Complete Assignments for CS231n: Convolutional Neural Networks for Visual Recognition

PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"

Place recognition with WiFi fingerprints using Autoencoders and Neural Networks

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

Contains my explorations of TensorFlow 2.x

由淺入深的深度學習資源 Collection of deep learning materials for everyone

Keras tutorial for beginners (using TF backend)

Machine Learning for High Energy Physics.

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

🧑‍🏫 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, ... 🧠

Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks

Quiz & Assignment of Coursera

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