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66 search results found

Numerical Linear Algebra ⭐ 9,850

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

Ml Foundations ⭐ 2,224

Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science

Linear Algebra With Python ⭐ 2,160

Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.

Deeplearningbook Notes ⭐ 1,432

Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)

Hackermath ⭐ 1,339

Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way

Tutorials ⭐ 847

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

Precourse ⭐ 587

A repo for the pre-course work at home exercises

18.335 - Introduction to Numerical Methods course

Basic Mathematics For Machine Learning ⭐ 418

The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI

Pilot course for Robotics 101: Computational Linear Algebra

A blazing fast matrix library for Elixir/Erlang with C implementation using CBLAS.

100daysofmlcode ⭐ 302

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings 👍

Xtensor Blas ⭐ 150

BLAS extension to xtensor

18.303 - Linear PDEs course

Swift library like numpy, playgrounds notebook like jupyter.

Engcomp4_landlinear ⭐ 104

Using computational thinking to get deep insights on the foundations of linear algebra

Quant Notes ⭐ 101

Quantitative Interview Preparation Guide, updated version here ==>

Python Graphblas ⭐ 95

Python library for GraphBLAS: high-performance sparse linear algebra for scalable graph analytics

Numerical_linear_algebra ⭐ 79

Julia code for the book Numerical Linear Algebra

Introduction To Python Numerical Analysis For Engineers And Scientist ⭐ 69

Introduction to Python: Numerical Analysis for Engineers and Scientist. In 2017, Python became the world's most popular programming language. This course covers the basic syntax, linear algebra, plotting, and more to prepare students for solving numerical problems with Python.

Undergraduate In Statistics ⭐ 59

Using Computer with your Statistics Major Course

Nagpythonexamples ⭐ 52

Examples and demos showing how to call functions from the NAG Library for Python

Vmls Companions ⭐ 52

*This is a companion to the companion for: "Introduction to Applied Linear Algebra" by Boyd and Vandenberghe.

Publications ⭐ 42

My publications on Medium

Mathematics For Machine Learning And Data Science Specialization Coursera ⭐ 42

Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes

Numerics Notes ⭐ 40

Slides/notes and Jupyter notebook demos for an introductory course of numerical analysis/scientific computing

Chen 3170 ⭐ 37

Computational Methods in Chemical Engineering (UMass Lowell, Spring 2024); Prof. Valmor F. de Almeida.

Mathematics_for_machine_learning ⭐ 32

Learn the mathematics behind machine learning and explore various mathematical concepts within machine learning.

Mathematics For Machine Learning And Data Science Specialization ⭐ 25

Non-credit online course by DeepLearning.AI

Cncc 2019 ⭐ 24

Computational Neuroscience Crash Course (CNCC 2019)

Notebooks 3m1 ⭐ 23

Jupyter notebooks (Python) for the course 3M1 at the Department of Engineering, University of Cambridge

HiCMA: Hierarchical Computations on Manycore Architectures

Julia Data Science ⭐ 20

Data science and numerical computing with Julia

Cncc 2020 ⭐ 20

Computational Neuroscience Crash Course (University of Bordeaux, 2020)

Pydata 2019 ⭐ 19

Materials for the Presentation "A Crash Course in in Applied Linear Algebra"

Linear_algebra_for_quantum_computing ⭐ 18

This is course material for a course on linear algebra and mathematical prerequisites for quantum computing. It contains Jupyter notebooks and Python scripts that can be downloaded as part of the course.

Foundations of Machine Learning Course Materials.

Coursera Imperial College Of London Mathematics For Machine Learning Specialization ⭐ 16

This Repository contains Solutions to the Quizes & Lab Assignments of the Mathematics for Machine Learning Specialization offered by Imperial College of London on Coursera taught by David Dye, Samuel J. Cooper, A. Freddie Page, Marc Peter Deisenroth

Numerical_linear_algebra_notebooks ⭐ 16

IPython notebooks with supplementary material to accompany the textbook by Trefethen & Bau.

Launchpad ⭐ 14

Resources to get started in Quantum Computing!

Linalg For Ds ⭐ 14

Linear Algebra and Optimization for Data Science

Math App Ml ⭐ 13

Essential mathematics for applied machine learning and data science

Pythonforrusers ⭐ 13

Notebooks to introduce R users to Python

Math For Ml ⭐ 12

Mathematical preliminaries for machine learning

Linear regression to perform predictive analysis on individual's income.

Linear Algebra With Python ⭐ 12

w/ khan academy & coding the matrix

Deeplearninghandbook ⭐ 12

Lecture Slides and Programming Exercises that may help study the deep learning book by Goodfellow, Bengio and Courville.

Ds Scriptsnook ⭐ 11

🎊One Stop Destination to get acquainted with scripts in Data Science. Turn yourself into a pro. Show your support by ✨ this repository.

Ia Maths Jupyter ⭐ 11

Notebooks in support of of the Part IA (Michaelmas Term) mathematics course at the Department of Engineering at University of Cambridge

Introduction To Numpy Matplotlib Tensorflow ⭐ 11

NumPy fundamentals for tensor computation; Matplotlib for data visualization

Ta Sessions ⭐ 11

This repository includes codes related with the FGV EMAp lectures which I worked as teacher assitant.

Mathematics For Machine Learning ⭐ 10

This repository contains the code for all the programming tasks of the Mathematics for Machine Learning courses taught at Coursera by Imperial College London

Various Data Science Scripts ⭐ 10

A collection of coding scripts, notes, and mini-projects with reference to a series of Data Science, Web Development, programming concepts and foundations, and miscellaneous tech topics.

Machine Learning Lecture Notes ⭐ 9

Lecture notes and codes for machine learning

Dl Playground ⭐ 9

Exercises & challenges for aspiring deep learners

Ce125 Linear Algebra ⭐ 8

Linear Algebra Course Materials

Linear_algebra ⭐ 8

Linear Algebra documentaion and resource details

Numerical_optimization_of_ai ⭐ 7

Numerical techniques for optimization of artificial Intelligence

Numerical Linear Algebra ⭐ 7

A course on Linear Algebra using Python in Jupyter notebooks

Hessianfree ⭐ 7

On the New method of Hessian-free second-order optimization

Linear Algebra ⭐ 6

Computational Intelligence Slides Fall 2020 ⭐ 6

This is a course materials for the Fall 2020 class on Computational Intelligence (with a heavy focus on Linear Algebra and Convex Optimization tools, according to the needs of the student curriculum)

Introduction To Data Analyst And Data Science ⭐ 6

Introduction to Data Analyst and Data Science for Beginners

Numerics Review ⭐ 6

Jupyter notebooks with answers to end of chapter review questions for the textbook Scientific Computing by Michael Heath (2018).

Mathematics For Machine Learning And Data Science Specialization ⭐ 5

Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.

Linear Algebra for Machine Learning Book Exercises

Sensitivity Analysis Of Shock Distributions ⭐ 5

The purpose of this project is to model and quantify the changes in network linkages of the world economy using sensitivity analysis.

Fundamentals ⭐ 5

During my research, I happen to enjoy implementing algorithms from scratch. Through Fundamentals, I like to share my experiences with others.

Decart_advanced_python_2018 ⭐ 5

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