linear-regression
There are 9201 repositories under linear-regression topic.
Avik-Jain/100-Days-Of-ML-Code
100 Days of ML Coding
nfmcclure/tensorflow_cookbook
Code for Tensorflow Machine Learning Cookbook
cantaro86/Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
greyhatguy007/Machine-Learning-Specialization-Coursera
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
BinRoot/TensorFlow-Book
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
susanli2016/Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
zotroneneis/machine_learning_basics
Plain python implementations of basic machine learning algorithms
jostmey/NakedTensor
Bare bone examples of machine learning in TensorFlow
edyoda/data-science-complete-tutorial
For extensive instructor led learning
YunYang1994/TensorFlow2.0-Examples
🙄 Difficult algorithm, Simple code.
justmarkham/DAT8
General Assembly's 2015 Data Science course in Washington, DC
trekhleb/machine-learning-octave
🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained
nickgillian/grt
gesture recognition toolkit
kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis
Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall
cod3licious/autofeat
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
Ryota-Kawamura/Mathematics-for-Machine-Learning-and-Data-Science-Specialization
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.
abess-team/abess
Fast Best-Subset Selection Library
sajari/regression
Multivariable regression library in Go
Vaibhav/Stock-Analysis
Regression, Scrapers, and Visualization
JuliaStats/MultivariateStats.jl
A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)
tsuirak/deeplearning.ai
该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。
jmartinezheras/2018-MachineLearning-Lectures-ESA
Machine Learning Lectures at the European Space Agency (ESA) in 2018
rishal-hurbans/Grokking-Artificial-Intelligence-Algorithms
The official code repository supporting the book, Grokking Artificial Intelligence Algorithms
jayshah19949596/Machine-Learning-Models
Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means
NishkarshRaj/100DaysofMLCode
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 :+1:
a-martyn/ISL-python
Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources
Compendium of free ML reading resources
Suji04/ML_from_Scratch
Implementation of basic ML algorithms from scratch in python...
R-js/blasjs
Pure Javascript manually written :ok_hand: implementation of BLAS, Many numerical software applications use BLAS computations, including Armadillo, LAPACK, LINPACK, GNU Octave, Mathematica, MATLAB, NumPy, R, and Julia.
amanovishnu/ineuron-full-stack-data-science-assignments
this repository features assignments and projects from the iNeuron full stack data science course, providing valuable resources for learners to enhance their skills and apply their knowledge.
fukuball/fuku-ml
Simple machine learning library / 簡單易用的機器學習套件
jxareas/Machine-Learning-Notebooks
The full collection of Jupyter Notebook labs from Andrew Ng's Machine Learning Specialization.
PacktWorkshops/The-Python-Workshop
A New, Interactive Approach to Learning Python
emilwallner/Deep-Learning-From-Scratch
Six snippets of code that made deep learning what it is today.
HuangCongQing/MachineLearning_Ng
吴恩达机器学习coursera课程，学习代码(2017年秋) The Stanford Coursera course on MachineLearning with Andrew Ng
harunurrashid97/100-Days-Of-ML-Code
A day to day plan for this challenge. Covers both theoritical and practical aspects