Beginning with Machine Learning & Data Science in Python

Link: best udemy course Beginning with Machine Learning & Data Science in Python Fundamentals of Data Science: Exploratory Data Analysis (EDA), Regression (Linear & logistic), Visualization, Basic ML by UNP United Network of Professionals What you'll learn You will be able to apply data science algorithms for solving industry problems You will have a clear understanding of industry standards and best practices for predictive model building You will be able to derive key insights from data using exploratory data analysis techniques You will be able to efficiently handle data in a structured way using Pandas You will have a strong foundation of linear regression, multiple regression and logistic regression You will be able to use python scikit-learn for building different types of regression models You will be able to use cross validation techniques for comparing models, select parameters You will know about common pitfalls in modeling like over-fitting, bias-variance trade off etc.. You will be able to regularize models for reliable predictions Description 85% of data science problems are solved using exploratory data analysis (EDA), visualization, regression (linear & logistic). Naturally, 85% of the interview questions comes from these topics as well. This is a concise course created by UNP to focus on what matter most. This course will help you create a solid foundation of the essential topics of data science.