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