Machine Learning Training Course Content


Week 1


Introduction to Python Programming Language

  • Lists
  • Sets
  • Tuples
  • Dictionaries

Week 2


Introduction to Python for Data Science

  • Numpy
  • Pandas
  • Advanced Pandas Tricks
  • Exploratory Data Analysis
  • Data Cleaning
  • Data Preparation

Week 3


Introduction to Data Analysis

  • Groupby
  • Aggregate Functions
  • Lambas
  • Functions
  • Classes
  • Definitions
  • Filter
  • Matrices
  • Queries
  • Data Frame Operations

Week 4


Introduction to Data Visualization

  • Introduction to Pandas for Plotting
  • Types of Charts
  • Univariate Analysis
  • Bivariate Analysis
  • Multivariate Analysis
  • Matplotlib
  • Seaborn
  • Plotly
  • Animated Data Visualizations
  • Geo Spatial Data Visualizations
  • Creating Dashboards in Python

Week 5


Introduction to Data Preprocessing

  • Feature Engineering
  • Feature Extraction
  • Feature Selection Strategies
  • Types of Feature Selection
  • Correlation
  • Heatmaps
  • Data Preparation
  • Data Manipulation

Week 6


Introduction to Machine Learning

  • Introduction to Types of Machine Learning
  • Supervised Learning Techniques
  • Regression Analysis
  • Linear Regression
  • Lasso Regression
  • Ridge Regression
  • Elastic Net Regression
  • Metrics for Regression

Week 7


Introduction to Classification Algorithms

  • Logistic Regression
  • Decision Trees
  • Random Forests
  • K Nearest Neighbors
  • Support Vector Machines
  • Naive Bayes Theorem
  • Ada Boost
  • Metrics for Classification

Week 8


Introduction to Unsupervised Learning

  • Types of Clustering Techniques
  • K-Means Clustering
  • Hierarchial Clustering
  • Dimensionality Reduction Techniques
  • PCA
  • LDA
  • Difference between LDA and PCA

Week 9


Introduction to Advanced Machine Learning Tricks

  • Cross Validation Techniques
  • Grid Search
  • Hyper Parameter Tuning
  • Ensembling Techniques
  • Model Validation Techniques
  • Model Explanation


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