Python With Data Science

? Using Modules

? Listing Methods in a Module

? Creating Your Own Modules

? List Comprehension

? Dictionary Comprehension

? String Comprehension

? Python 2 vs Python 3

? Sets (Python 3+)

? Python Idioms

? Python Data Science ?Ecosystem?

? NumPy

? NumPy Arrays

? NumPy Idioms

? pandas

? Data Wrangling with pandas' DataFrame

? SciPy

? Scikit-learn

? SciPy or scikit-learn?

? Matplotlib

? Python vs R

? Python on Apache Spark

? Python Dev Tools and REPLs

? Anaconda

? IPython

? Visual Studio Code

? Jupyter

? Jupyter Basic Commands

? Summary

? What is Data Science?

? Data Science Ecosystem

? Data Mining vs. Data Science

? Business Analytics vs. Data Science

? Data Science, Machine Learning, AI?

? Who is a Data Scientist?

? Data Science Skill Sets Venn Diagram

? Data Scientists at Work

? Examples of Data Science Projects

? An Example of a Data Product

? Applied Data Science at Google

? Data Science Gotchas

? Summary

? Big Data Analytics Pipeline

? Data Discovery Phase

? Data Harvesting Phase

? Data Priming Phase

? Data Logistics and Data Governance

? Exploratory Data Analysis

? Model Planning Phase

? Model Building Phase

? Communicating the Results

? Production Roll-out

? Summary

? Repairing and Normalizing Data

? Dealing with the Missing Data

? Sample Data Set

? Getting Info on Null Data

? Dropping a Column

? Interpolating Missing Data in pandas

? Replacing the Missing Values with the Mean Value

? Scaling (Normalizing) the Data

? Data Preprocessing with scikit-learn

? Scaling with the scale() Function

? The MinMaxScaler Object

? Summary

? Descriptive Statistics

? Non-uniformity of a Probability Distribution

? Using NumPy for Calculating Descriptive Statistics Measures

? Finding Min and Max in NumPy

? Using pandas for Calculating Descriptive Statistics Measures

? Correlation

? Regression and Correlation

? Covariance

? Getting Pairwise Correlation and Covariance Measures

? Finding Min and Max in pandas DataFrame

? Summary

? Data Aggregation and Grouping

? Sample Data Set

? The pandas.core.groupby.SeriesGroupBy Object

? Grouping by Two or More Columns

? Emulating the SQL's WHERE Clause

? The Pivot Tables

? Cross-Tabulation

? Summary

? Data Visualization
? What is matplotlib?
? Getting Started with matplotlib
? The Plotting Window
? The Figure Options
? The matplotlib.pyplot.plot() Function
? The matplotlib.pyplot.bar() Function
? The matplotlib.pyplot.pie () Function
? Subplots
? Using the matplotlib.gridspec.GridSpec Object
? The matplotlib.pyplot.subplot() Function
? Hands-on Exercise
? Figures
? Saving Figures to File
? Visualization with pandas
? Working with matplotlib in Jupyter Notebooks
? Summary

? Data Science, Machine Learning, AI?

? Types of Machine Learning

? Terminology: Features and Observations

? Continuous and Categorical Features (Variables)

? Terminology: Axis

? The scikit-learn Package

? scikit-learn Estimators

? Models, Estimators, and Predictors

? Common Distance Metrics

? The Euclidean Metric

? The LIBSVM format

? Scaling of the Features

? The Curse of Dimensionality

? Supervised vs Unsupervised Machine Learning

? Supervised Machine Learning Algorithms

? Unsupervised Machine Learning Algorithms

? Choose the Right Algorithm

? Life-cycles of Machine Learning Development

? Data Split for Training and Test Data Sets

? Data Splitting in scikit-learn

? Hands-on Exercise

? Classification Examples

? Classifying with k-Nearest Neighbors (SL)

? k-Nearest Neighbors Algorithm

? k-Nearest Neighbors Algorithm

? The Error Rate

? Hands-on Exercise

? Dimensionality Reduction

? The Advantages of Dimensionality Reduction

? Principal component analysis (PCA)

? Hands-on Exercise

? Data Blending

? Decision Trees (SL)

? Decision Tree Terminology

? Decision Tree Classification in Context of Information Theory

? Information Entropy Defined

? The Shannon Entropy Formula

? The Simplified Decision Tree Algorithm

? Using Decision Trees

? Random Forests

? SVM

? Naive Bayes Classifier (SL)

? Naive Bayesian Probabilistic Model in a Nutshell

? Bayes Formula

? Classification of Documents with Naive Bayes

? Unsupervised Learning Type: Clustering

? Clustering Examples

? k-Means Clustering (UL)

? k-Means Clustering in a Nutshell

? k-Means Characteristics

? Regression Analysis

? Simple Linear Regression Model

? Linear vs Non-Linear Regression

? Linear Regression Illustration

? Major Underlying Assumptions for Regression Analysis

? Least-Squares Method (LSM)

? Locally Weighted Linear Regression

? Regression Models in Excel

? Multiple Regression Analysis

? Logistic Regression

? Regression vs Classification

? Time-Series Analysis

? Decomposing Time-Series

? Summary

Lab 1 - Learning the Lab Environment

Lab 2 - Using Jupyter Notebook

Lab 3 - Repairing and Normalizing Data

Lab 4 - Computing Descriptive Statistics

Lab 5 - Data Grouping and Aggregation

Lab 6 - Data Visualization with matplotlib

Lab 7 - Data Splitting

Lab 8 - k-Nearest Neighbors Algorithm

Lab 9 - The k-means Algorithm

Lab 10 - The Random Forest Algorithm