A concise resource repository for machine learning bookmarks. Here, It'll remain concise but yet to comprehensive for machine learning resources and related stuff. It'll be updated continually with times. However, ML-Bookmarks is still of its early stage. There're lots of modification of this repository still remain. We need your support and constructive feedback to turn this repository more robust and reliable to everyone 😊
Some of the material is not reviewed fully yet. A section like this will be revised in the near future. % will represent completeness.
- Data Set | 50%
- Book Materials | 90%
- Online Course | 90%
- Research Databases | 40%
- GitHub | 50%
- Kaggle | 60%
- Best Blog | 80%
- YouTube Star | 60%
For more details, please follow this link. Mr. Stacy Stanford has done a great job. However, here are some best source to find high quality dataset so far:
Some of the most influential book lists in the concerned field.
Machine Learning (ML)
- Hands-On ML with Scikit-Learn, Keras, and TensorFlow | Author: Aurélien
- Python Machine Learning | Author: Sebastian
- The Hundred-Page Machine Learning Book | Author: Andriy
Deep Learning
- Deep Learning | Author: Ian Goodfellow
- Deep Learning with Python | Author: Francois
- Deep Learning for Computer Vision with Python | Author: Adrain
- Reinforcement Learning: An Introduction | Author: Richard
Data Science
- Data Mining: Concepts and Techniques
- An Introduction to Statistical Learning: with Applications in R
- Python for Data Analysis
- Learning Spark: Lightning-Fast Big Data Analysis
- High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark
Some of the most influential high rated and promising MOOC courses.
Machine Learning
- ML Crash Course | Google
- ML | Coursera
- ML Specialization | Coursera
- ML Foundations: A Case Study Approach
- ML: Regression
- ML: Classification
- ML: Clustering & Retrieval
- Mathematics for ML Specialization | Coursera
- Mathematics for ML: Linear Algebra
- Mathematics for ML: Multivariate Calculus
- Mathematics for ML: PCA
- Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization | Coursera
- End-to-End ML with TensorFlow on GCP
- Production ML Systems
- Image Understanding with TensorFlow on GCP
- Sequence Models for Time Series and NLP
- Applying ML to your Data with GCP | Coursera
- ML Fundamentals | edX
- Intro to ML | Udacity
- ML A-Z™ | Udemy
- ML with Javascript | Udemy
Deep Learning
- UFLDL Tutorial
- Stanford Teaching
- Stanford CS | CNN for Visual Recognition
- Stanford CS | NLP with Deep Learning
- Deep Learning Specialization | Coursera
- Neural Networks and Deep Learning
- Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
- Structuring Machine Learning Projects
- Convolutional Neural Networks
- Sequence Models
- Deep Learning | Udacity
- Deep Learning A-Z™ | Udemy
- Complete Guide to TensorFlow for Deep Learning with Python | Udemy
- NLP - Natural Language Processing with Python | Udemy
- Python for Computer Vision with OpenCV and Deep Learning | Udemy
- Deep Learning Computer Vision™ CNN, OpenCV, YOLO, SSD & GANs | Udemy
- TensorFlow 2.0 | Udemy
Data Science
- Python for Data Science | edX
- Big Data Specialization | Coursera
- Introduction to Big Data
- Big Data Modeling and Management Systems
- Big Data Integration and Processing
- ML With Big Data
- Graph Analytics for Big Data
- Big Data - Capstone Project
- Data Engineering, Big Data, and ML on GCP Specialization | Coursera
- Google Cloud Platform Big Data and Machine Learning Fundamentals
- Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform
- Serverless Data Analysis with Google BigQuery and Cloud Dataflow
- Serverless Machine Learning with Tensorflow on Google Cloud Platform
- Building Resilient Streaming Systems on Google Cloud Platform
- Modern Big Data Analysis with SQL Specialization | Coursera
- Foundations for Big Data Analysis with SQL
- Analyzing Big Data with SQL
- Managing Big Data in Clusters and Cloud Storage
- Python for Data Science and Machine Learning Bootcamp | Udemy
- Spark and Python for Big Data with PySpark | Udemy
- Scala and Spark for Big Data and Machine Learning | Udemy
Some enrich online research databases.
A very few amount of interesting projects and some relevant sources.
| Interested Projects | Research Paper | Explained Blogs |
|---|---|---|
| ReinforceJs | - | Doc |
| Neural-Doodle | Arxiv | - |
| Quantum-Game | - | http://quantumgame.io/ |
| Xcessiv | - | Doc |
| CAM | Arxiv | Doc |
| Sketch Code | - | Doc |
| - | - | - |
Very few amount of interesting kaggle competiton.
- For Beginners
- Moderate
Very few amount of amazing blogs.
- Google AI Blog
- Berkeley AI Research
- Depth First Learning
- Polo Club of Data Science
- OpenAI
- Research Blog: Stanford NLP
- Cleverhans | About: Security and privacy in machine learning.
- Andrej Karpathy
- Kevin Zakka
- Arthur Juliani
- Colah
- Michael Nielsen
- Sebastian Ruder
- PyImageSearch
- Machine Learning Mastery
- Open Source
- Siraj Raval
- 3Blue1Brown
- Edureka
- Sentdex
- Standford School | CNN for Visual Recognition
- Code Bullet
- Khan Academy
If there's anything you would like to inform me here or if you're just feeling social, feel free to email me or reach out on LinkedIn.