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內(nèi)容簡介

　　從事Amazon和IMDB的機器學習算法相關(guān)工作的Frank Kane將指導(dǎo)你邁向數(shù)據(jù)科學世界的第一步?！秾嵱脭?shù)據(jù)科學和Python機器學習（影印版）》為你提供了理解和探究該領(lǐng)域核心主題所需的工具，以及構(gòu)建和分析你自己的機器學習模型的信心和實踐。借助有趣易懂的實例，F(xiàn)rank Kane以任何人都能理解的方式解釋了貝葉斯方法和K-means聚類等潛在的復(fù)雜主題?；贔rank大獲成功的數(shù)據(jù)科學課程，《實用數(shù)據(jù)科學和Python機器學習（影印版）》將使你能夠使用Python分析數(shù)據(jù)并高效地執(zhí)行機器學習。Frank會使用Python所提供的各種數(shù)據(jù)挖掘和數(shù)據(jù)分析技術(shù)幫助你挖掘數(shù)據(jù)的價值，開發(fā)有效的預(yù)測模型來預(yù)測未來的結(jié)果。你還將學習到如何使用Apache Spark對大數(shù)據(jù)開展大規(guī)模的機器學習。書中涵蓋了準備待分析的數(shù)據(jù)、訓練機器學習模型以及可視化最終數(shù)據(jù)分析。

作者簡介

　　My name is Frank Kane. I spent nine years at ******， corn and imdb. corn， wrangling millionsof customer ratings and customer transactions to produce things such as personalizedrecommendations for movies and products and people who bought this also bought. I tellyou， I wish we had Apache Spark back then， when I spent years trying to solve theseproblems there. I hold 17 issued patents in the fields of distributed computing， data mining，and machine learning. In 2012， I left to start my own successful company， Sundog Software，which focuses on virtual reality environment technology， and teaching others about bigdata analysis.

圖書目錄

Preface
Chapter 1：Getting Started
Installing Enthought Canopy
Giving the installation a test run
If you occasionally get problems opening your IPNYB files
Using and understanding IPython（Jupyter）Notebooks
Python basics-Part 1
Understanding Python code
Importing modules
Data structures
Experimenting with Iists
Pre colon
Post colon
Negative syntax
Adding list to list
The append function
Complex data structures
Dereferencing a single element
The sort function
Reverse sort
Tuples
Dereferencing an element
List of tuples
Dictionaries
lterating through entries
Python basics-Part 2
Functions in Python
Lambda functions-functional programming
Understanding boolean expressions
The if statement
The if-else loop
Looping
The while loop
Exploring activity
Running Python scripts
More options than just the lPython，Jupyter Notebook
Running Python scripts in command prompt
Using the Canopy I DE
Summary
Chapter 2：Statistics and Probability Refresher，and Python Practice
Types of data
NumericaI data
Discrete data
Continuous data
Categorical data
OrdinaI data
Mean，median，and mode
Mean
Median
The factor of outliers
Mode
Using mean，median，and mode in Python
Calculating mean using the NumPy package
Visualizing data using matplotlib
Calculating median using the NumPy package
Analyzing the effect of outliers
Calculating mode using the SciPy package
Some exercises
Standard deviation and variance
Variance
Measuring variance
Standard deviation
Identifying outliers with standard deviation
Population variance versus sample variance
The Mathematical explanation
Analyzing standard deviation and variance on a histogram
Using Python to compute standard deviation and variance
Try it yourself
Probability density function and probability mass function
The probability density function and probability mass functions
Probability density functions
Probability mass functions
Types of data distributions
Uniform distribution
Normal or Gaussian distribution
The exponential probability distribution or Power law
Binomial probability mass function
Poisson probability mass function
……
Chapter 3：Matplotlib and Advanced Probability Concepts
ChantAr 4：Predictive ModeIs
Chapter 5：Machine Learning with Pvthon
Chapter 6：Recommender Systems
Chapter 7：More Data Mininq and Machine Learninq Techniaues
ChaDter 8：Dealing with Real．World Data
Chapter 9：Apache Spark-Machine Learning on Big Data
Chapter 10：Testing and Experimental Design
Index