Compilation of Deep Learning Resources
- Online Tutorials (beginner to advanced)
- TensorFlow Tutorial (Basic)
- TensorFlow Hub Tutorial (Pre-trained Models)
- PyTorch Tutorial (Basic)
- Kaggle Tutorial (Intro to Deep Learning)
- RealPython (How to build a Neural Network)
- Machine Learning Mastery (Deep Learning in Python with Keras)
- DataCamp (Keras Tutorial using Python)
- Python Programming (Deep Learning basics with Python and TensorFlow)
- DeepLizard (Deep Learning Fundamental)
- SimpliLearn (Deep Learning Intro with Python)
- Machine Learning Crash Course (TensorFlow APIs)
- TensorFlow Example for Beginner (GitHub)
- Full Stack Deep Learning (2021 Course)
- GitHub Deep Learning (TensorFlow Course)
- Deep Learning University Courses (Deep Learning Drizzle)
- Deep Learning (Video Lectures)
- Keras Code Examples (Keras.io)
- Keras layers API (preprocessing etc)
- Keras Models API (sequential and functional model)
- Keras Applications (models for prediction, feature extraction, and fine-tuning)
- Platform/Package (most popular)
- Tensorflow 2 (Machine Learning Platform)
- Keras (Python Deep Learning Framework)
- PyTorch (Python Machine Learning Framework)
- DeepLearning4j (open-source deep learning library for the JVM)
- H2O.ai (open-source machine learning platform for the enterprise)
- scikit-learn (open-source machine learning library in Python)
- NVIDIA CUDA-X AI (deep learning software stack to build high performance GPU-accelerated applications)
- OpenCV (deep learning module in OpenCV)
- Apache Spark MLlib (distributed deep learning with TensorFlow)
- Apache Singa (distributed deep learning library)
- AutoKeras (AutoML system based on Keras)
- Chainer (framework of neural networks for deep learning)
- MATLAB Deep Learning Toolbox (MathWorks)
- Datasets (open data)
- Pathmind (curated datasets for deep learning and machine learning)
- Kaggle Datasets (open competition datasets)
- Dataset Search (Google Research)
- Open Images Dataset (~9M images annotated with labels)
- TensorFlow Datasets (collection of datasets ready to use with TensorFlow or other Python ML frameworks)
- Machine Learning Models (ready to deploy)
- Tensorflow Hub (Text, Image, Video and Audio problem domains)
- Image Classification Modules (Google)
- Hugging Face (state of the art NLP models)
- PapersWithCode (state of the art ML models from publications)
- Toolkit
- TensorBoard (TensorFlow’s visualization toolkit)
- KerasTuner (scalable hyperparameter optimization framework)
- TensorFlow Playground (interactive visualization of neural networks)
- CNN Explainer (Convolutional Neural Network [CNN] in your browser)
- KerasCV (state-of-the-art pipelines for image classification, object detection, image segmentation etc.)
- KerasNLP (natural language processing library that supports users through their entire development cycle)
- Glossary
- Machine Learning Glossary (Google Developer)
- Deep Learning Glossary (wildML)
- 25 Deep Learning Terms for Beginners (analyticsvidhya)
- Common Machine Learning Terminology (Springboard)
- Machine Learning Glossary Cheat-Sheet
- Troubleshooting (solve your coding problems)
- StackOverflow (deep learning technical questions)
- Strategy for Deep Learning Troubleshooting
- 37 Reasons why your Neural Network is not working
- Deep Dive Into Error Analysis (neptune.ai)
- Facebook Group (make friends)
- Cheat-Sheet Compilation (direct download)
- Deep learning cheat sheet (DeepLearningMY)
- Building a Data Pipeline for Deep Learning (NetApp)
- Jobs
- Deep Learning Jobs in Malaysia (Jobstreet)
- Deep Learning Job Skills (Indeed)
- Deep Learning Skill Salary (Malaysia)
- Data Scientist Job Analytics (DeepLearningMY)
# Feel free to add more resources in the comment section below 🙂
(Last updated: 1 March 2023)
