#Linear-regression
Showing 60 of 106 repositories tagged #linear-regression, ranked by stars
100 Days of ML Coding
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
Collection of notebooks about quantitative finance, with interactive python code.
Code for Tensorflow Machine Learning Cookbook
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Plain python implementations of basic machine learning algorithms
For extensive instructor led learning
๐ Difficult algorithm, Simple code.
General Assembly's 2015 Data Science course in Washington, DC
๐ค MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained
gesture recognition toolkit
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
Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where youโll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
Compendium of free ML reading resources
Fast Best-Subset Selection Library
The full collection of Jupyter Notebook labs from Andrew Ng's Machine Learning Specialization.
The official code repository supporting the book, Grokking Artificial Intelligence Algorithms
Multivariable regression library in Go
Regression, Scrapers, and Visualization
Machine Learning Lectures at the European Space Agency (ESA) in 2018
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
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:
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.
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.
Simple machine learning library / ็ฐกๅฎๆ็จ็ๆฉๅจๅญธ็ฟๅฅไปถ
A New, Interactive Approach to Learning Python
Estudo e implementaรงรฃo dos principais algoritmos de Machine Learning em Jupyter Notebooks.
A day to day plan for this challenge. Covers both theoritical and practical aspects
Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset
Machine learning algorithms in Dart programming language
Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.
This repository contains implementations of all Machine Learning Algorithms from scratch in Python. Mathematics required for ML and many projects have also been included.
Code for Java Deep Learning Cookbook
Aulas da Escola de Inteligรชncia Artificial de Sรฃo Paulo
๐ฆ BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.
This repository explores the variety of techniques and algorithms commonly used in deep learning and the implementation in MATLAB and PYTHON
Machine Learning Concepts with Concepts
Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language
A book on the mathematical foundations of AI from an engineering perspective.
Linear Regression Model for Real State House Price Prediction
A simple machine learning framework written in Swift ๐ค
Lesson material on data science and machine learning topics/concepts
Source files for "Fun Q: A Functional Introduction to Machine Learning in Q"
piecewise-regression (aka segmented regression) in python. For fitting straight line models to data with one or more breakpoints where the gradient changes.
Built house price prediction model using linear regression and k nearest neighbors and used machine learning techniques like ridge, lasso, and gradient descent for optimization in Python
A platform for deep learning challenges and AI education. Deep-ML is a website dedicated to making deep learning challenges accessible and engaging. It offers a variety of AI-related problems for learners at different skill levels.
โณ๏ธ PASS: Amazon Web Services Certified (AWS Certified) Machine Learning Specialty (MLS-C01) by learning based on our Questions & Answers (Q&A) Practice Tests Exams.
A simple Web application developed in order to provide the farmers/users an approximation on how much amount of crop yield will be produced depending upon the given input
Machine Learning - Linear Regression_Ecommerce_Prediction
A New Interactive Approach to Learning Data Analysis
Collection of various implementations and Codes in Machine Learning, Deep Learning and Computer Vision โจ๐ฅ
By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
Stock price trend prediction with news sentiment analysis using deep learning
A simple implementation of the LOESS algorithm using numpy
This repository contains all the programming exercises in Python for the Coursera course called "Machine Learning" by Adjunct Professor Andrew Ng at Stanford University.
Machine Learning Procedures and Functions for Neo4j
Using Computer with your Statistics Major Course
I will update this repository to learn Machine learning with python with statistics content and materials
๐ค Python implementations of some of the fundamental Machine Learning models and algorithms from scratch with interactive Jupyter demos and math being explained.