MEGA Launch - 105+ New System Design Case Studies
With Complete Design and Code Implementation. For your tech interviews With examples and code..
Hi All,
Join us in celebrating the successful launch of our highly praised System Design Series and Case Studies! We are excited to introduce a fresh collection of case studies designed specifically to equip you with the knowledge and skills needed to excel in your upcoming system design interviews. Get ready to make the most of this opportunity and enhance your preparation to new heights!
Github for System Design Interviews with Case Studies
Coming soon- ML System Design Series. Follow and subscribe today!
Let’s get started with new system design case studies-
More system design case studies coming soon! Follow - Link
Things you must know in System Design -
System design basics : https://bit.ly/3SuUR0Y
Horizontal and vertical scaling : https://bit.ly/3slq5xh
Load balancing and Message queues: https://bit.ly/3sp0FP4
High level design and low level design, Consistent Hashing, Monolithic and Microservices architecture : https://bit.ly/3DnEfEm
Caching, Indexing, Proxies : https://bit.ly/3SvyVDc
Networking, How Browsers work, Content Network Delivery ( CDN) : https://bit.ly/3TOHQRb
Database Sharding, CAP Theorem, Database schema Design : https://bit.ly/3CZtfLN
Concurrency, API, Components + OOP + Abstraction : https://bit.ly/3sqQrhj
Estimation and Planning, Performance : https://bit.ly/3z9dSPN
Map Reduce, Patterns and Microservices : https://bit.ly/3zcsfmv
SQL vs NoSQL and Cloud : https://bit.ly/3z8Aa49
Read more —Data Science using Python
Data Visualization
Statistics
Data Collection and Data Cleaning
Data Manipulation
Linear Algebra for Machine Learning
Supervised Learning
Regression
Ridge Regression
Bayesian Methods
Classification Algorithms
Logistic Regression
Support Vector Machines and Decision Trees
Boosting and K-Means Clustering
Unsupervised Learning
Clustering Methods
K-means,
Principal Component Analysis and Markov Models
Hidden Markov Models and Kalman Filtering
Modeling
Model selection and evaluation
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