This is the code repository for Hands-On Data Science and Python Machine Learning, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.
Join Frank Kane, who worked on Amazon and IMDb’s machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them.
Based on Frank’s successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis.
All of the code used in the book are present here. Following is a example of the code block used in the book:
import numpy as np
import pandas as pd
from sklearn import tree
input_file = "c:/spark/DataScience/PastHires.csv"
df = pd.read_csv(input_file, header = 0)
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