MIT-Machine Learning with Python–From Linear Models to Deep Learning

Overview

MIT-Machine Learning with Python–From Linear Models to Deep Learning | One of the 5 courses in MIT MicroMasters in Statistics & Data Science

Welcome to 6.86x Machine Learning with Python–From Linear Models to Deep Learning.

Machine learning methods are commonly used across engineering and sciences, from computer systems to physics. Moreover, commercial sites such as search engines, recommender systems (e.g., Netflix, Amazon), advertisers, and financial institutions employ machine learning algorithms for content recommendation, predicting customer behavior, compliance, or risk.

As a discipline, machine learning tries to design and understand computer programs that learn from experience for the purpose of prediction or control.

In this course, you will learn about principles and algorithms for turning training data into effective automated predictions. We will cover:

-Representation, over-fitting, regularization, generalization, VC dimension;

-Clustering, classification, recommender problems, probabilistic modeling, reinforcement learning;

-On-line algorithms, support vector machines, and neural networks/deep learning.

You will be able to:

  1. Understand principles behind machine learning problems such as classification, regression, clustering, and reinforcement learning

  2. Implement and analyze models such as linear models, kernel machines, neural networks, and graphical models

  3. Choose suitable models for different applications

  4. Implement and organize machine learning projects, from training, validation, parameter tuning, to feature engineering

You will implement and experiment with the algorithms in several Python projects designed for different practical applications.

cuML - RAPIDS Machine Learning Library

cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t

RAPIDS 3.1k Dec 28, 2022
Crypto-trading - ML techiques are used to forecast short term returns in 14 popular cryptocurrencies

Crypto-trading - ML techiques are used to forecast short term returns in 14 popular cryptocurrencies. We have amassed a dataset of millions of rows of high-frequency market data dating back to 2018 w

Panagiotis (Panos) Mavritsakis 4 Sep 22, 2022
A collection of Scikit-Learn compatible time series transformers and tools.

tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p

Chris Santiago 0 Mar 30, 2022
Predict the income for each percentile of the population (Python) - FRENCH

05.income-prediction Predict the income for each percentile of the population (Python) - FRENCH Effectuez une prédiction de revenus Prérequis Pour ce

1 Feb 13, 2022
Titanic Traveller Survivability Prediction

The aim of the mini project is predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and more.

John Phillip 0 Jan 20, 2022
Machine learning that just works, for effortless production applications

Machine learning that just works, for effortless production applications

Elisha Yadgaran 16 Sep 02, 2022
A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize

⚡ funk-svd funk-svd is a Python 3 library implementing a fast version of the famous SVD algorithm popularized by Simon Funk during the Neflix Prize co

Geoffrey Bolmier 171 Dec 19, 2022
Data Efficient Decision Making

Data Efficient Decision Making

Microsoft 197 Jan 06, 2023
Both social media sentiment and stock market data are crucial for stock price prediction

Relating-Social-Media-to-Stock-Movement-Public - We explore the application of Machine Learning for predicting the return of the stock by using the information of stock returns. A trading strategy ba

Vishal Singh Parmar 15 Oct 29, 2022
虚拟货币(BTC、ETH)炒币量化系统项目。在一版本的基础上加入了趋势判断

🎉 第二版本 🎉 (现货趋势网格) 介绍 在第一版本的基础上 趋势判断,不在固定点位开单,选择更优的开仓点位 优势: 🎉 简单易上手 安全(不用将api_secret告诉他人) 如何启动 修改app目录下的authorization文件

幸福村的码农 250 Jan 07, 2023
Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

DataCanvas 216 Dec 23, 2022
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber

Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber

EconML/CausalML KDD 2021 Tutorial 124 Dec 28, 2022
jaxfg - Factor graph-based nonlinear optimization library for JAX.

Factor graphs + nonlinear optimization in JAX

Brent Yi 134 Dec 21, 2022
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis.

Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.

Jeong-Yoon Lee 720 Dec 25, 2022
A GitHub action that suggests type annotations for Python using machine learning.

Typilus: Suggest Python Type Annotations A GitHub action that suggests type annotations for Python using machine learning. This action makes suggestio

40 Sep 18, 2022
Python package for stacking (machine learning technique)

vecstack Python package for stacking (stacked generalization) featuring lightweight functional API and fully compatible scikit-learn API Convenient wa

Igor Ivanov 671 Dec 25, 2022
Price forecasting of SGB and IRFC Bonds and comparing there returns

Project_Bonds Project Title : Price forecasting of SGB and IRFC Bonds and comparing there returns. Introduction of the Project The 2008-09 global fina

Tishya S 1 Oct 28, 2021
Binary Classification Problem with Machine Learning

Binary Classification Problem with Machine Learning Solving Approach: 1) Ultimate Goal of the Assignment: This assignment is about solving a binary cl

Dinesh Mali 0 Jan 20, 2022
2D fluid simulation implementation of Jos Stam paper on real-time fuild dynamics, including some suggested extensions.

Fluid Simulation Usage Download this repo and store it in your computer. Open a terminal and go to the root directory of this folder. Make sure you ha

Mariana Ávalos Arce 5 Dec 02, 2022
A library to generate synthetic time series data by easy-to-use factors and generator

timeseries-generator This repository consists of a python packages that generates synthetic time series dataset in a generic way (under /timeseries_ge

Nike Inc. 87 Dec 20, 2022