अभ्यास • Week 08

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Weekly Production Deliverable

Target Output

Deliverable: Binary Search on 1D arrays done. All 8 Verbal Ability topics complete. Your ml-from-scratch repo exists, with a working Linear Regression + Gradient Descent implementation you wrote yourself.

Weeks: W06 W07 W08 Active W09 W10

Monday

0 / 2 done

DSA Search X in sorted array; Lower Bound

1.5h

AI/ML Linear Regression: Math & Simple Model

CampusX: Simple Linear Regression, cost function, Ordinary Least Squares (OLS) closed-form solution vs Gradient Descent intuition

2.5h

Tuesday

0 / 2 done

DSA Upper Bound; Search Insert Position

1.5h

CORE Editing & Merging Data

INSERT, UPSERT, UPDATE, DELETE, ALTER, TRUNCATE + Unions in SQL (UNION, UNION ALL, INTERSECT) + solve: System Settings, Active/Archived Users, Combine Sales Records, Inactive Sellers

2.5h

Wednesday

0 / 2 done

DSA Floor and Ceil in a Sorted Array

1.5h

AI/ML Multiple Linear Regression & Gradient Descent

CampusX: Multiple Linear Regression, Batch Gradient Descent, Stochastic Gradient Descent, Mini-Batch Gradient Descent + StatQuest: "Linear Regression, Clearly Explained" & "Gradient Descent, Step-by-Step"

2.5h

Thursday

0 / 2 done

DSA First and Last Occurrence in sorted array

1.5h

CORE SQL Joins Deep Dive

INNER, LEFT, RIGHT, FULL OUTER, CROSS, SELF JOIN, ON vs WHERE + solve: Employees and Their Departments, Customer Orders Overview, Employees Earning More Than Manager

2.5h

Friday

0 / 2 done

DSA Search in Rotated Sorted Array-I and II

1.5h

AI/ML Regularization & Scratch Implementation

CampusX: Ridge (L2), Lasso (L1), ElasticNet + StatQuest: "Ridge vs Lasso" + Scratch implementation: Code Linear Regression with Gradient Descent in raw NumPy without scikit-learn; push to a new ml-from-scratch GitHub repo

2.5h

⚡ Weekend High-Load Execution • 8.0h Daily Deep Focus Lab

Saturday

0 / 3 done

DSA Find Minimum in Rotated Sorted Array; Find how many times it's rotated

1.5h

AI/ML ml-from-scratch Linear Regression Lab (4.0h)

Code Batch, Mini-Batch, and Stochastic Gradient Descent in raw NumPy from scratch with R² and MSE loss metrics.

4.0h

APT Quant M8 & Verbal

Quant M8 Ratio and Proportion (Basic & Advance) + Verbal: One Word Substitution (Basic & Advance — Verbal Ability complete!)

2.5h

Sunday

0 / 3 done

DSA Single element in a sorted array + revision: all Binary Search Fundamentals/Logic Building so far

1.5h

AI/ML Regularization & Polynomial Regression Lab (4.0h)

Implement L1 (Lasso) and L2 (Ridge) penalty terms from scratch in your NumPy Linear Regression; visualize decision boundaries and over-fitting.

4.0h

APT Logical & Joins Level-2

Logical: Alphanumeric Series (Basic & Advance) + Andrew Ng ML Spec Course 1 Week 2 + solve Level-2 Joins: Sales Analysis, Minimum Distance Between Points, Views in SQL

2.5h

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Week 08 Technical Notes & Journal

#LeetCode #Java #DSA #Week08