A Tour of Data Science: Learn R and Python in ParallelA Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. It does not cover everything, but rather, teaches the key concepts and topics in Data Science. It also covers two of the most popular programming languages used in Data Science, R and Python, in one source. Key features:
Appealing to data scientists, statisticians, quantitative analysts, and others who want to learn programming with R and Python from a data science perspective. |
Contents
| 1 | |
Chapter 2 More on RPython Programming | 37 |
Chapter 3 data table and pandas | 71 |
Chapter 4 Random Variables Distributions Linear Regression | 99 |
Chapter 5 Optimization in Practice | 133 |
Chapter 6 Machine Learning A gentle introduction | 161 |
| 203 | |
| 205 | |
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Common terms and phrases
algorithms alpha apply argument array basic better calculate called carb chapter column convex optimization create data structure data.table debug decision define denote depth distribution drat elements Engineering environment equal estimate evaluation example FALSE follows function Gaussian gear given gradient hypothesis implementation import numpy initialize instance iter join Let’s linear regression loss machine learning matrix Mazda RX4 mean memory method minimize module mtcars_dt multiple node normal NULL numpy as np object observations Operations optimization package pandas parameters performance points prediction probability problem programming Python qsec R/Python random variable range rmse rows sample script seconds single solution solve specify step structure tree true update usually vector y_hat