अभ्यास • Week 14

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Weekly Production Deliverable

Target Output

Deliverable: Linked List (Logic Building + FAQs Medium) done. Unsupervised learning (K-Means, Hierarchical, DBSCAN, PCA) done. You have a real Kaggle submission.

Weeks: W11 W12 W13 W14 Active W15

Monday

0 / 2 done

DSA Add two numbers in LL; Segregate odd and even nodes

1.5h

AI/ML Unsupervised 1: K-Means Clustering

CampusX: K-Means algorithm, centroid initialization (K-Means++), Elbow Method (WCSS), Silhouette Score + StatQuest: "K-Means Clustering" + Scratch implementation: Code K-Means in raw NumPy; add to ml-from-scratch

2.5h

Tuesday

0 / 2 done

DSA Sort a LL of 0s, 1s, 2s; Remove Nth node from back

1.5h

CORE Memory Management & Allocation

Logical vs Physical Address space, Memory Management Unit (MMU), Swapping, Contiguous Allocation, Fragmentation (Internal vs External), Compaction & Buddy System + Quiz

2.5h

Wednesday

0 / 2 done

DSA Reverse a LL

1.5h

AI/ML Unsupervised 2: Hierarchical & DBSCAN

CampusX: Hierarchical Clustering (Agglomerative, Divisive, Linkage methods: Single, Complete, Average, Ward), Dendrograms + DBSCAN (Density-Based Spatial Clustering: Core, Border, Noise points, ε , MinPts)

2.5h

Thursday

0 / 2 done

DSA Add one to number in LL; Find middle of LL

1.5h

CORE Paging & Segmentation

Paging concept, Page Table structure, Frames, Page Table Entries, Multilevel Paging, Inverted Page Table, TLB in Operating System (Translation Lookaside Buffer, TLB Hit/Miss ratio, Effective Memory Access Time - EMAT), Segmentation + Quiz

2.5h

Friday

0 / 2 done

DSA Delete middle node in LL; Check if LL is palindrome

1.5h

AI/ML Dimensionality Reduction: PCA & Kaggle Submission

CampusX: Principal Component Analysis (PCA), variance maximization, covariance matrix, eigenvectors & eigenvalues + StatQuest: "PCA Step-by-Step" + Kaggle: Build, tune, and submit your first full competition entry

2.5h

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

Saturday

0 / 3 done

DSA Find intersection of Y LL; Detect a loop in LL

1.5h

AI/ML ml-from-scratch K-Means Clustering Lab (4.0h)

Implement K-Means algorithm with random initialization and inertia computation; plot Elbow curve and Silhouette score.

4.0h

APT Quant M14 & Verbal

Quant M14 Profit and Loss (Basic & Advance) + Verbal: Mixed Practice

2.5h

Sunday

0 / 3 done

DSA Starting point of loop in LL; Length of loop + revision

1.5h

AI/ML PCA & Dimensionality Reduction Lab (4.0h)

Implement PCA via Eigenvalue Decomposition of Covariance Matrix in NumPy; project high-dimensional data (MNIST) to 2D.

4.0h

APT Logical & Virtual Memory

Logical: Clocks (Basic & Advance — Logical Reasoning complete!) + Virtual Memory, Demand Paging, Page Faults, Page Replacement Algorithms (FIFO, Optimal, LRU, LFU, Clock), Belady's Anomaly, Thrashing

2.5h

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Week 14 Technical Notes & Journal

#LeetCode #Java #DSA #Week14