Python for Data Science and Machine Learning for Beginners
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2
Installing Anaconda on Windows
FREE PREVIEW
Installing Anaconda on MacOs
Installing Librairies in Python
Jupyter Notebooks and Spyder
3
Basics Python
Loops in Python
Functions and variables in Python
Modules in Python
4
Basics of NumPy
NumPy functions
NumPy Array manipulations
NumPy Array reshaping and concatenation
More Operations in NumPy Array
5
Introduction to Pandas
Pandas Series
Pandas Data Frame (Part 1)
Pandas Data Frame (Part 2)
Dealing with missing values using Pandas
6
Introduction to matplotlib
Drawing and saving figures
Matplotlib Subplots
Parameter tuning for better visualization
Scatter plots and Histograms
7
Basic statistical operations
Exploratory analysis
Chi square test in Python
Analysis of Variances (ANOVA)
Sampling
8
How Linear Regression works
Linear Regression in Python
How Naive Bayes work
Naive Bayes with Python
How KNN works
KNN in Python
How Logistic Regression works
Logistic Regression in Python
Decision Trees in Python
How Decision trees works
How Random Forest works
Random Forest in Python
How K-means clustering works
K-means clustering in Python
How SVM works
SVM in Python
How Neural Networks works
Neural Networks in Python
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10.3. Feature selection and Label encoding
10.1. Dealing with outliers
10.4. Hyperparameter tuning
10.2. Dealing with missing values