دانلود کتاب Data Science Handbook

فهرست مطالب :

Cover
Half-Title Page
Series Page
Title Page
Copyright Page
Dedication
Contents
Acknowledgment
Preface
1 Data Munging Basics
1 Introduction
1.1 Filtering and Selecting Data
1.2 Treating Missing Values
1.3 Removing Duplicatesduplicates
1.4 Concatenating and Transforming Data
1.5 Grouping and Data Aggregation
References
2 Data Visualization
2.1 Creating Standard Plots (Line, Bar, Pie)
2.2 Defining Elements of a Plot
2.3 Plot Formatting Segment 3 Plot formatting
2.4 Creating Labels and Annotations
2.5 Creating Visualizations from Time Series Data
2.6 Constructing Histograms, Box Plots, and Scatter Plots
References
3 Basic Math and Statistics
3.1 Linear Algebra
3.2 Calculus
3.2.1 Differential Calculus
3.2.2 Integral Calculus
Statistics for Data Science
3.3 Inferential Statistics
3.3.1 Central Limit Theorem
3.3.2 Hypothesis Testing
3.3.3 ANOVA
3.3.4 Qualitative Data Analysis
3.4 Using NumPy to Perform Arithmetic Operations on Data
3.5 Generating Summary Statistics Using Pandas and Scipy
3.6 Summarizing Categorical Data Using Pandas
3.7 Starting with Parametric Methods in Pandas and Scipy
3.8 Delving Into Non-Parametric Methods Using Pandas and Scipy
3.9 Transforming Dataset Distributions
References
4 Introduction to Machine Learning
4.1 Introduction to Machine Learning
4.2 Types of Machine Learning Algorithms
4.3 Explanatory Factor Analysis
4.4 Principal Component Analysis (PCA)
References
5 Outlier Analysis
5.1 Extreme Value Analysis Using Univariate Methods
5.2 Multivariate Analysis for Outlier Detection
5.3 DBSCan Clustering to Identify Outliers
References
6 Cluster Analysis
6.1 K-Means Algorithm
6.2 Hierarchial Methods
6.3 Instance-Based Learning w/k-Nearest Neighbor
References
7 Network Analysis with NetworkX
7.1 Working with Graph Objects
7.2 Simulating a Social Network (ie; Directed Network Analysis)
7.3 Analyzing a Social Network
References
8 Basic Algorithmic Learning
8.1 Linear Regression
8.2 Logistic Regression
8.3 Naive Bayes Classifiers
References
9 Web-Based Data Visualizations with Plotly
9.1 Collaborative Analytics
9.2 Basic Charts
9.3 Statistical Charts
9.4 Plotly Maps
References
10 Web Scraping with Beautiful Soup
10.1 The BeautifulSoup Object
10.2 Exploring NavigableString Objects
10.3 Data Parsing
10.4 Web Scraping
10.5 Ensemble Models with Random Forests
References
11 Covid19 Detection and Prediction
Bibliography
12 Leaf Disease Detection
Bibliography
13 Brain Tumor Detection with Data Science
Bibliography
14 Color Detection with Python
Bibliography
15 Detecting Parkinson’s Disease
Bibliography
16 Sentiment Analysis
Bibliography
17 Road Lane Line Detection
Bibliography
18 Fake News Detection
Bibliography
19 Speech Emotion Recognition
Bibliography
20 Gender and Age Detection with Data Science
Bibliography
21 Diabetic Retinopathy
Bibliography
22 Driver Drowsiness Detection in Python
Bibliography
23 Chatbot Using Python
Bibliography
24 Handwritten Digit Recognition Project
Bibliography
25 Image Caption Generator Project in Python
Bibliography
26 Credit Card Fraud Detection Project
Bibliography
27 Movie Recommendation System
Bibliography
28 Customer Segmentation
Bibliography
29 Breast Cancer Classification
Bibliography
30 Traffic Signs Recognition
Bibliography
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