Machine Learning in Finance: From Theory to Practice Book

Advances in Financial Machine Learning

Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Models that explain the returns of individual stocks generally use company and stock characteristics, e.g., the market prices of financial instruments and companies’ accounting data. These characteristics can also be used to predict expected stock returns out-of-sample. Most studies use simple linear models to form these predictions [1] or [2]. An increasing body of academic literature documents that more sophisticated tools from the Machine Learning (ML) and Deep Learning (DL) repertoire, which allow for nonlinear predictor interactions, can improve the stock return forecasts [3], [4] or [5]. The main goal of this project is to investigate whether modern DL techniques can be utilized to more efficiently predict the movements of the stock market. Specifically, we train a LSTM neural network with time series price-volume data and compare its out-of-sample return predictability with the performance of a simple logistic regression (our baseline model).

Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python

💰 A collection of finance related machine learning examples

Using ML to extract campaign finance data from messy forms for journalism

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Best free, open-source datasets for data science and machine learning projects. Top government data including census, economic, financial, agricultural, image datasets, labeled and unlabeled, autonomous car datasets, and much more. Data.gov NOAA - https://www.ncdc.noaa.gov/cdo-web/ atmospheric, ocean Bureau of Labor Statistics - https://www.bls.gov/data/ employment, inflation US Census Data - https://www.census.gov/data.html demographics, income, geo, time series Bureau of Economic Analysis - http://www.bea.gov/data/gdp/gross-dom... GDP, corporate profits, savings rates Federal Reserve - https://fred.stlouisfed.org/ curency, interest rates, payroll Quandl - https://www.quandl.com/ financial and economic Data.gov.uk UK Dataservice - https://www.ukdataservice.ac.uk Census data and much more WorldBank - https://datacatalog.worldbank.org census, demographics, geographic, health, income, GDP IMF - https://www.imf.org/en/Data economic, currency, finance, commodities, time series OpenData.go.ke Kenya govt data on agriculture, education, water, health, finance, … https://data.world/ Open Data for Africa - http://dataportal.opendataforafrica.org/ agriculture, energy, environment, industry, … Kaggle - https://www.kaggle.com/datasets A huge variety of different datasets Amazon Reviews - https://snap.stanford.edu/data/web-Am... 35M product reviews from 6.6M users GroupLens - https://grouplens.org/datasets/moviel... 20M movie ratings Yelp Reviews - https://www.yelp.com/dataset 6.7M reviews, pictures, businesses IMDB Reviews - http://ai.stanford.edu/~amaas/data/se... 25k Movie reviews Twitter Sentiment 140 - http://help.sentiment140.com/for-stud... 160k Tweets Airbnb - http://insideairbnb.com/get-the-data.... A TON of data by geo UCI ML Datasets - http://mlr.cs.umass.edu/ml/ iris, wine, abalone, heart disease, poker hands, …. Enron Email dataset - http://www.cs.cmu.edu/~enron/ 500k emails from 150 people From 2001 energy scandal. See the movie: The Smartest Guys in the Room. Spambase - https://archive.ics.uci.edu/ml/datase... Emails Jeopardy Questions - https://www.reddit.com/r/datasets/com... 200k Questions and answers in json Gutenberg Ebooks - http://www.gutenberg.org/wiki/Gutenbe... Large collection of books

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Calculate technical indicators from historical stock data Create features and targets out of the historical stock data. Prepare features for linear models, xgboost models, and neural network models. Use linear models, decision trees, random forests, and neural networks to predict the future price of stocks in the US markets. Evaluate performance of the models in order to optimize them Get predictions with enough accuracy to make a stock trading strategy profitable.

The course is divided into 3 main parts covering python programming fundamentals, financial analysis in Python and AI/ML application in Finance/Banking Industry.

Note about cousera online course: ml and rl in finance

Machine Learning for Quantitative Finance

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A project for financial risk classification of more than 500 companies. We forecast the ratings given by agencies such as Moody's and Standard and Poors.

A project that uses machine learning techniques to build a backtesting engine for trading and to analyze stock market data and make predictions.

The specialization provides the knowledge and practical skills necessary to develop a strong foundation on core paradigms of machine learning, with a focus on applications of ML to various practical problems in Finance

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A simple finance tracker built during MLH GHW AI/ML Week.

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A scalable, declarative, low-code framework for real-time and batch feature calculation/management (quant finance, anomaly/fraud detection, etc.), predictive ML training/inference and simulation. Built on top of Ray

A curated collection of 10+ end-to-end AI/ML/DL projects showcasing real-world problem-solving, data analysis, and model deployment using Streamlit. Each project demonstrates the use of cutting-edge algorithms in healthcare, finance, NLP, and computer vision. Perfect for learning, inspiration.

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Knowledgebase— a collection of information for quantitative finance, insurance, mathematics and AI—This serves as a sprawling notebook of books, papers, code links and Jupyter notebooks across quantitative finance, insurance, AI/ML, coding/IT, maths, probability and applied statistics, organised in subject-tree folders rather than a software repo.

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Finance planner app to track and calculate finance info from expenses, banking, investments, savings, insurance and get advice from AI features. Developed with MERN, Firebase, Go, GraphQL, Redis, Postgresql, and ML based APIs.

ML for GL - A complete Julialang ERP Data Science framework for Finance, Supply chain accounting

Final project for CS3892 - Big Data

Machine Learning and Reinforcement Learning in Finance Specialization (MOOC) Assignments

Code (Jupyter Notebooks) for Coursera - Machine Learning and Reinforcement Learning in Finance Specialization