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data-science-awesome-reference
Daftar referensi tautan-tautan berguna untuk mempelajari tentang Data Science, Machine Learning, dan lainnya. Reference list of useful links to learn about Data Science, Machine Learning and more.
https://github.com/pr0b35/data-science-awesome-reference
- Intro Data Science with Siuba
- AI Expert Roadmap
- Introduction to AI
- Welcome to Introduction to Machine Learning for Coders! taught by Jeremy Howard
- Machine Learning From Scratch
- FOUNDATIONS OF MACHINE LEARNING by Bloomberg
- Introduction to Machine Learning
- Machine learning cheat sheet
- Create machine learning models by Microsoft
- Coursera : Machine Learning by AndrewNg
- Stanford CS 229 ― Machine Learning
- Coursera Machine Learning Foundations: A Case Study Approach
- Introduction to Data Science and Machine Learning
- The Missing Semester of Your CS Education by MIT
- Stanford CS229: Machine Learning | Autumn 2018
- Introduction to Machine Learning by Google
- Tabular Data by Machine Learning University
- Stat 451: Intro to Machine Learning (Fall 2020)
- 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
- Best open-access datasets for machine learning, data science, sentiment analysis, computer vision, natural language processing (NLP), clinical data, and others.
- Guide to Awesome Machine Learning Projects
- The Movies Dataset
- ML X ART creative machine learning experiments
- ML ArtLine
- ML Example Projects by Paperwithcode
- 10 ML Beginner Projects
- Ten minutes to learn Linear regression for dummies!!!
- Statistics 101: Linear Regression, The Very Basics 📈
- Linear Regression Concept
- The Simple Linear Regression Explanation
- Machine Learning Decision Tree
- Classification with TensorFlow
- How to Get Started With Recommender Systems
- Machine Learning and NLP for Students and Practitioners
- Recommendations for Getting Started with NLP
- Standford CS224n: Natural Language Processing with Deep Learning
- CMU Multilingual NLP 2020
- How to use ML to search photos by natural language?
- Tracking Progress in Natural Language Processing
- NLP Best Practices
- Modern Deep Learning Techniques Applied to Natural Language Processing
- Build, train and deploy state of the art models powered by the reference open source in natural language processing.
- The Big Bad NLP Database
- A Survey of Surveys (NLP & ML)
- A Recipe for Training Neural Networks
- Convolutional Neural Nets: Foundations, Computations, and New Applications by Cornell University
- Non-linearities in Neural Networks
- MIT 6.S191 Introduction to Deep Learning
- Literature of Deep Learning for Graphs
- Awesome Pytorch List
- ML Visuals
- Deep Learning (with PyTorch)
- Deep Learning for Computer Vision
- Lectures for UC Berkeley CS 285: Deep Reinforcement Learning.
- Full Stack Deep Learning Youtube Channel
- Python Basics : Learn Python Programming
- Coursera Algorithms Specialization
- Google's Python Class
- PYTHONINDO
- BELAJARPYTHON
- FreeCodeCamp Introduction to Python for Everybody
- Python Getting Started
- Python Basic Exercise for Beginners
- Beginner Python exercises
- Edabit Python Challenges
- NumPy Illustrated: The Visual Guide to NumPy
- Learning Python for Data Analysis and Visualization
- Code Combat
- Introduction to TensorFlow
- Machine Learning Crash Course
- Lectures of Linear Algebra with Python
- Best-of Machine Learning with Python
- Harvard CS109 Data Science
- Linear Regression in Python
- Coursera Statistics with Python Specialization
- Introduction to Linear Algebra for Applied Machine Learning with Python
- Linear Regression for Absolute Beginners with Implementation in Python!
- Khan Academy : Linear Algebra
- Ritchieng : Linear Algebra for Machine Learning
- DIDL : Linear Algebra
- Pabloinsente : Linear Algebra
- MIT Open Courseware : Linear Algebra
- Mathematics for Machine Learning - Linear Algebra
- StatQuest : Statistics Fundamentals
- Udacity : Intro to Statistics
- StatQuest : Linear Regression & Linear Model
- EDX Data Science: Probability
- An Intuitive Introduction to Probability
- Probabilistic Machine Learning: An Introduction
- EDX MathTrackX: Differential Calculus
- ML Glossary : Calculus
- Youtube Channel KALKULUS
- Mathematics for Machine Learning - Multivariate Calculus by Imperial College London
- The Matrix Calculus You Need For Deep Learning by Cornell University
- Proof Index Mathematics Course
- Computer Science courses with video lectures
- 10 Machine Learning Youtube Videos by Santiago
- Coursera Introduction to Complex Analysis
- Coursera Information Theory
- Coursera Data Mining Specialization
- Coursera Mathematics for Machine Learning Specialization
- MIT Missing Semester IAP 2020
- The Hundred Page Machine Learning Book
- Ebook Programming Gratis by DeepTech
- Mathematics for Machine Learning Ebook Pdf
- ML / AI Books Recommendation
- Bayesian Books Recommendation
- Programming Recommendation Books
- Rekomendasi Buku Python Bahasa Indonesia by DeepTech Twitter
- Amazon Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD
- Data Science Learning Path
- Path to a free self-taught education in Data Science! by Open Source Society University
- Course Recommendations for Introductory Machine Learning
- Homemade Machine Learning
- Kumpulan kuliah bagus di Stanford untuk menjadi data scientist yang sakti mandraguna
- Machine Learning, Deep Learning, and Computer Vision References
- 15 Trending Data Science GitHub Repositories you can not miss in 2017
- 10 Popular Data Science Resources on Github
- Github Data-Science-References
- Github Data Science Collected Resources
- Github Data-Science-Resources
- 50 FREE Artificial Intelligence, Computer Science, Engineering and Programming Courses from the Ivy League Universities
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