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DSA & Fullstack System Design Interview Preparation

In-depth DSA Patterns, DSA Problems, Frontend LLD, Frontend HLD, Backend LLD, Backend HLD, and AI/ML System Design write-ups for FAANG-style interview prep.

Web Technologies

DSA Patterns

  • DSA Patterns

    Subsets and Permutations Problem Solving Patterns in Java

    Comprehensive guide to subset and permutation generation algorithms with iterative and recursive approaches, including time complexity analysis and practical implementation strategies.

  • DSA Patterns

    Finding Medians and Percentiles in Data Streams

    Comprehensive guide to solving median and percentile problems using heaps, binary search, and sliding window techniques in Java.

DSA Problems

  • DSA Problems

    Minimum Number of Vertices to Reach All Nodes

    Find the minimum set of vertices needed to reach all nodes in a directed acyclic graph using topological sorting and in-degree analysis.

  • DSA Problems

    Flood Fill Algorithm Implementation and Analysis

    Complete Java solution for flood fill algorithm with BFS/DFS approaches, time complexity analysis, and practical implementation considerations for FAANG interviews.

  • DSA Problems

    Max Area of Island Java Solution

    Complete Java implementation for finding maximum area of island in 2D grid using DFS and BFS approaches with time and space complexity analysis.

Frontend LLD

Frontend HLD

  • Frontend HLD

    Frontend Code Splitting and Lazy Loading Strategy Design

    Comprehensive high-level design for implementing efficient code splitting and lazy loading in modern web applications to optimize performance and user experience.

  • Frontend HLD

    Fast Initial Page Load Application Design

    Comprehensive frontend high-level design for optimizing application startup performance with code splitting, caching, and preloading strategies

  • Frontend HLD

    Frontend Performance Optimization Strategy Design

    Comprehensive HLD document outlining scalable frontend performance optimization techniques, resource loading strategies, and implementation patterns for high-impact web applications.

  • Backend LLD

    CQRS Framework Design and Implementation

    Comprehensive low-level design for a Command Query Responsibility Segregation (CQRS) framework with event sourcing, read/write model separation, and distributed consistency patterns.

AI/ML System Design

  • AI/ML System Design

    Matrix Factorization and Collaborative Filtering System Design

    Comprehensive AI/ML system design for recommendation engines using matrix factorization and collaborative filtering techniques with production-ready architecture considerations

  • AI/ML System Design

    Gradient Boosting Machine Design and Implementation

    Comprehensive system design document for gradient boosting frameworks including XGBoost and LightGBM architectures, trade-offs, and production implementation strategies.

  • AI/ML System Design

    Large-Scale Logistic Regression Scoring System Design

    Comprehensive system design for scalable logistic regression inference at enterprise scale with distributed computing and real-time scoring capabilities.

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