roessland / learning-from-dataLinks
Caltech Machine Learning course notes and homework. Implements from scratch algorithms like SVM, neural networks, backpropagation, perceptrons and other linear classifiers.
☆47Updated 6 years ago
Alternatives and similar repositories for learning-from-data
Users that are interested in learning-from-data are comparing it to the libraries listed below
Sorting:
- Assignments (Python) in Algorithms Courses of Stanford University at Coursera☆61Updated 6 years ago
- Exercises and solutions to Stanford CS229 Machine Learning in Python☆206Updated 2 years ago
- STAT 451: Intro to Machine Learning @ UW-Madison (Fall 2020)☆445Updated last year
- Solutions to 'An Introduction to Statistical Learning with Applications in R'... in Python!☆35Updated last year
- Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.☆344Updated last year
- Notes of MITx 6.86x - Machine Learning with Python: from Linear Models to Deep Learning☆332Updated last year
- Implementation of basic mathematical pattern recognition/machine learning techniques for fun☆133Updated 3 years ago
- All notes and materials for the CS229: Machine Learning course by Stanford University☆251Updated 4 years ago
- This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Fais…☆295Updated 5 years ago
- Solutions to the problems in the book: Linear Algebra and Learning from Data by Gilbert Strang, MIT☆299Updated 3 years ago
- Python code (in the form of Jupyter ipython notebooks) to support the book "Math and Architectures of Deep Learning" (Krishnendu Chaudhur…☆223Updated last year
- ☆47Updated 3 years ago
- Repository of my solutions to the problems of "Learning from Data"☆277Updated 5 years ago
- ☆188Updated 7 years ago
- .pdf Format Books for Machine and Deep Learning☆251Updated 7 years ago
- ☆203Updated 3 years ago
- A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book☆903Updated 4 years ago
- Inside Deep Learning: The math, the algorithms, the models☆270Updated 2 years ago
- Machine learning course materials.☆577Updated 2 years ago
- Solutions to Wasserman's 'All of Statistics'.☆104Updated 6 years ago
- Solutions for All of Statistics by Wasserman☆13Updated 4 years ago
- Beginner Python course from Harvard University on edX☆51Updated 6 years ago
- An Introduction to Statistical Learning with Applications in PYTHON☆551Updated 3 years ago
- Second edition of Springer Book Python for Probability, Statistics, and Machine Learning☆369Updated 4 years ago
- Repo for MIT 6.036 Machine Learning☆30Updated 4 years ago
- Solutions to the exercises in Grinstead and Snell's Introduction to Probability☆92Updated 2 years ago
- My own notes, implementations, and musings for MIT's graduate course in machine learning, 6.867☆342Updated last year
- Notebook for quick search☆86Updated 7 years ago
- Documenting my progress as I work through The Elements of Statistical Learning book by T. Hastie, R. Tibshirani, and J. Friedman☆61Updated 5 years ago
- Data Mining - University of Illinois at Urbana-Champaign☆109Updated 2 years ago