There are 40 repositories under linear-regression topic.
100 Days of ML Coding
Code for Tensorflow Machine Learning Cookbook
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Collection of notebooks about quantitative finance, with interactive python code.
Plain python implementations of basic machine learning algorithms
Python code for common Machine Learning Algorithms
Bare bone examples of machine learning in TensorFlow
🙄 Difficult algorithm, Simple code.
General Assembly's 2015 Data Science course in Washington, DC
For extensive instructor led learning
gesture recognition toolkit
🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained
Regression, Scrapers, and Visualization
Machine Learning Lectures at the European Space Agency (ESA) in 2018
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
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。
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.
Fast Best-Subset Selection Library
Six snippets of code that made deep learning what it is today.
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
Launch machine learning models into production using flask, docker etc.
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:
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
A New, Interactive Approach to Learning Python
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
A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.
A day to day plan for this challenge. Covers both theoritical and practical aspects
Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
Aulas da Escola de Inteligência Artificial de São Paulo
Code for Java Deep Learning Cookbook
Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz
Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.