Data Analytics I: Statistics and Machine Learning in Python with Examples and Applications

by Daniel Rösch

Data Analytics, Statistics and Machine Learning in Python with many Examples and Real World Applications for Financial Data Analytics, Text and Image Processing, Stock Return Prediction with News, House Price Modeling, Face Recognition and more Series 1 Fundamentals of Data - Exploratory Data Analytics - Equality and Performance Measurement - Text and Image Processing - Stochastic and Probability Foundations - Statistical Learning - Parameter Estimation - Statistical Tests - Bayesian Statistics - Regression - Regression Diagnostics - Analysis of Variance (ANOVA) - Generalized Linear ModelsSeries 2 Machine Learning Principles – Workflow – Feature Engineering - Learning, Validation and Prediction – Under- and Overfit – Train-Test-Split - Crossvalidation – Hyperparameter tuning - Supervised Machine Learning for Regression and Classification– K-Nearest Neighbors – Decision Trees – Bootstrapping – Bagging – Random Forests - Boosting – Neural Networks – Unsupervised Learning – Clustering – Principal Components Analysis - Fallacies

Kindle Edition

Published November 1, 2020