Machine Learning with Python

Section 1: Introduction to Machine Learning

 Welcome

 Introduction to Machine Learning

 Python for Machine Learning

 Supervised vs. Unsupervised

Section 2: Python 3.0 ( Crash Course )

 Spark Databox's Master Python crash course - Self-paced video training.

Section 3: Regression

 Scikit-Learn

 EDA

 Correlation Analysis and Feature Selection

 Correlation Analysis and Feature Selection

 Linear Regression with Scikit-Learn

 Five Steps Machine Learning Process

 Robust Regression

 Evaluate Regression Model Performance

 Multiple Regression 1

 Multiple Regression 2

 Regularized Regression

 Polynomial Regression

 Dealing with Non-linear Relationships

 Feature Importance

 Data Preprocessing

 Variance-Bias Trade-Off

 Learning Curve

 Cross-Validation

 CV Illustration

Section 4: Classification

 Logistic Regression

 Introduction to Classification

 Understanding MNIST

 SGD

 Performance Measure and Stratified k-Fold

 Confusion Matrix

 Precision

 Recall

 f1

 Precision-Recall Tradeoff

 Altering the Precision-Recall Tradeoff

 ROC

Section 5: Support Vector Machine (SVM)

 Support Vector Machine (SVM) Concepts

 Linear SVM Classification

 Polynomial Kernel

 Radial Basis Function

 Support Vector Regression

Section 6: Tree

 Introduction to Decision Tree

 Training and Visualizing a Decision Tree

 Visualizing Boundary

 Tree Regression, Regularization and Over Fitting

 End to End Modeling

 Project HR

 Project HR with Google Colab

Section 7: Ensemble Machine Learning

 Ensemble Learning Methods Introduction

 Bagging

 Random Forests and Extra-Trees

 AdaBoost

 Gradient Boosting Machine

 XGBoost Installation

 XGBoost

 Project HR - Human Resources Analytics

 Ensemble of Ensembles Part 1

 Ensemble of ensembles Part 2

Section 8: Clustering

 Intro to Clustering

 Intro to k-Means

 More on k-Means

 Intro to Hierarchical Clustering

 More on Hierarchical Clustering

 DBSCAN

Section 9: k-Nearest Neighbours (kNN)

 kNN Introduction

 Project Cancer Detection

Section 10: Dimensional Reduction

 Dimensionality Reduction Concept

 PCA Introduction

 Project Wine

 Kernel PCA

 Kernel PCA Demo

 LDA vs. PCA

 Project Abalone

Section 11: Real-time project

 Machine Learning With Python project environment setup

 Real-time Machine Learning With Python project

 Project demonstration

 Expert evaluation and feedback

Section 12: You made it!!

 Spark Databox Machine Learning With Python certification

 Interview preparation

 Mock interviews

 Resume preparation

 Knowledge sharing with industry experts

 Counseling to guide you to the right path in Machine Learning With Python career