Machine Learning Classification Mastery

Master the most widely used Machine Learning technique

45 learners enrolled

Language: English

Instructors: Kunaal Naik

₹9999 including GST

PREVIEW

Why this course?

Description

Course Curriculum

Data Science Profile
KYC Form
Data Science profile
Setup Code/Data/Environment
Setup Code & Data with Anaconda (5:00)
Setup Data 7 Code with Google Colab (7:00)
Introduction
Who can take this course? (2:00) Preview
Industry Gaps in Data Science (9:00) Preview
Our Methodology for teaching Data Science (10:00)
Level of Classification Course (3:00)
ML Classification Projects (4:00)
Course Delivery Method (11:00)
Iterative Modelling Process
Exploration (2:00)
Stage 1 - Intuition based Base Model
Stage 1 Plan (5:00) Preview
Code 1 IF THEN Model (40:00)
Code2: Base Model with Missing Value Strategy (27:00)
Code3: Outlier Strategy (21:00)
Project 1 Completion Form
Code 1 to 3 Doubts/Feedback
Project 2 - Cohort Based Execution (Optional)
Project 3 - Going Solo! (Optional)
Stage 1 - Exploration (Optional)
Code1 Exploration (3:00)
Code2 Exploration (3:00)
Code3 Exploration (3:00)
Stage 2 - Improved Pipeline with Tree Based Models
Stage 2 Plan (5:00)
Code 4: Transformation Strategy (13:00)
Code 5: Combine Strategies (16:00)
Code 6: Decision Tree Pipeline (18:00)
Stage 2 Exploration (Optional)
Code4 Exploration (3:00)
Code5 Exploration (3:00)
Code6 Exploration (3:00)
Stage 2 Exploration Completion
Stage 3 - Improving Score
Week 3 Plan (5:00)
Code 7: Decision Tree Hyperparameter Optimization (28:00)
Code 8: Random Forest with Hyperparameter Optimization (25:00)
Code 9: Feature Engineering (25:00)
Stage 3 Exploration (Optional)
Code7 Exploration (3:00)
Code8 Exploration (3:00)
Code9 Exploration (3:00)
Stage 3 Exploration Completion
Stage 4: Gearing towards Project Completion
Feature Importance Variations (2:00)
One Hot Encoding without Pipeline (7:00)
Ordinal Encoding without Pipeline (5:00)
Ordinal Encoding with Pipeline (8:00)
One Hot Encoding with Pipeline (9:00)
Ordinal Encoding with Grid Search Pipeline (4:00)
Stage 5: Present Outcomes : One Liner
Presenting Outcomes (4:00) Preview
Google X Y Z Formula (2:00)
Google X Y Z Formula Example (3:00)
Writing Business Outcome (6:00)
Writing Model Outcome (4:00)
Using One Liners in Resume (4:00)
Stage 6: Present Outcomes: One Pager
What is a One Pager? (2:00) Preview
Business Objective & Solution (3:00)
Approach (4:00)
Who & Where (4:00)
Outcomes (2:00)
Adding Visual Elements (5:00)
Stage 7: Completion
Congratulations
What next?

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