Day 35 of System Design Case Studies Series : Design Telegram

Naina Chaturvedi

Aug 01, 2023

Complete Design with examples

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WHY you should take ONLY these courses to sky rocket your Data Science and ML Journey

Read about System Design 101 : Distributed Message Queue

Complete System Design Case Studies

Github : https://bit.ly/3jFzW01
Design Instagram
Design Robinhood
Design Twitter
Design Expedia
Design Paytm
Design ESPN
Design Lyft
Design URL Shortener
Design Agoda
Design Razorpay
Design Apple Music
Design CricHD
Design Dropbox
Design Doordash
Design Disney+Hotstar
Design Spotify
Design Wechat
Design Facebook Newsfeed
Design Netflix
Design Weibo
Design Medium.com
Design Alibaba
Design Substack
Design Splitwise
Design CashApp
Design Messenger App
Design Kayak
Design Bigbasket
Design Roblox
Design Coinbase
Design Google Drive
Design Swiggy
Design Trivago
Design ShareIt
Design OkCupid
Design Google Maps
Design Skyscanner
Design Duolingo
Design Food Panda
Design Saavn
Design Hacker Rank
Design Grab
Design Google Earth
Design Tinder
Design Coinbase Wallet
Design Trip.com
Design Pinterest
Design Amazon Prime Video
Design Twilio
Design Web Crawler
Design Google Docs
Design API Rate Limiter
Design HBO Max
Design Udacity
Design Meesho
Design Alipay
Design Zoom
Design Coursera
Design Baidu
Design Wikipedia
Design ShareChat
Design Hulu
Design Ticket Master
Design Trip Advisor
Design PubG
Design Microsoft Teams
Design MS Docs
Design Yelp
Design Cache Mechanism
Design Whatsapp
Design Distributed Cache
Design Book My Show
Design Zomato
Design FourSquare
Design Skype
Design Bumble
Design UberEats
Design Tiny URL
Design Groupme
Design Hinge
Design Codechef
Design Tiktok
Design Google Pay
Design Booking.com
Design Ola
Design Stock exchange Design System
Design Google Drive
Design Trivago
Design ShareIt
Design OkCupid
Design Reddit
Design Truecaller
Design One Drive
Design Webull
Design Hotstar
Design SoundCloud
Design Deliveroo
Design Lazada
Design Grubhub
Design Linkedin
Design Telegram
Design Leetcode
Design Snapchat
Design Instacart
Design Workday
Design Phonepe
Design Yandex
ML System Design Case Studies Series : https://bit.ly/3i5EDiH

Data Science using Python

Pandas
Numpy
Advanced Pandas Techniques
Data Pre-processing
Handling missing values
Data Cleaning
Mean/mode/median Imputation
Hot Deck Imputation
Rescale Data
Binarize Data
Regression Imputation
Stochastic regression imputation
Feature Scaling
Data Augmentation
Read and Process Large Datasets
Data Visualization basics
Data Visualization Projects
Data Visualization using Plotly and Bokeh
Data Profiling
Summary Functions
Indexing
Grouping
Linear Regression
Multi Linear Regression
Polynomial Regression
Regression
Support Vector Regression
Decision Tree Regression
Random Forest Regression
Feature Engineering
GroupBy Features
Categorical and Numerical Features
Missing Value Analysis
Fill the missing Values
Unique Value Analysis
Univariate Analysis
Bivariate Analysis
Multivariate Analysis
Correlation Analysis
Spearman’s ρ
Pearson’s r
Kendall’s τ
Cramér’s V (φc)
Phik (φk)

Data Visualization

Data Visualization basics
Data Visualization Projects
Data Visualization using Plotly and Bokeh

Statistics

Random Variables
Statistical Inferences
Probability
Standard deviation and variance
Statistical Distributions
Hypothesis Testing
Normal distribution
t-distribution
Bernoulli distribution
confidence intervals

Data Collection and Data Cleaning

Data Collection
Data Cleaning

Data Manipulation

Join
Melt
Cut
Transform
Clean
Slicing
Reshaping
Filter
Group by
Pivot and Merge
Concatenate
MultiIndexing
Stacking
Hierarchical indexing
Aggregate
Summarize data

Linear Algebra for Machine Learning

Linear algebra concepts in Python
Matrix operations
Advanced linear algebra procedures

Supervised Learning

Regression

Supervised learning with probabilistic models
linear regression
Ordinary Least Squares
Linear Models
Linear and Quadratic Discriminant Analysis
Support Vector Machines
Stochastic Gradient Descent
Nearest Neighbors
Gaussian Processes
Cross decomposition
Naive Bayes
Decision Trees
Ensemble methods
Feature selection

Ridge Regression

Bias-variance tradeoff
Regression analysis

Bayesian Methods

Lagrange multipliers tool
sparse regression model
estimate covariants
Bayesian linear regression

Classification Algorithms

Classification using nearest neighbors
K-nearest neighbors
Bayes classifier
Supervised learning classification
perceptron algorithm

Logistic Regression

Kernel Methods
Gaussian Processes
kernel
kernelized perceptron

Support Vector Machines and Decision Trees

Hyperplanes with maximum margin method
SVM
decision tree-based classifiers
Grid search hyperparameters

Boosting and K-Means Clustering

Bagging and boosting techniques
Characteristics of K-means tools
Label encoder

Unsupervised Learning

Clustering Methods
K-means,
soft K-means
Gaussian mixture model

Principal Component Analysis and Markov Models

PCA basics
Implement PCA
Implement Markov chains using quantecon

Hidden Markov Models and Kalman Filtering

Hidden Markov Model
Markov models
Gaussian models
Forward/backward algorithm

Modeling

Model Training and Evaluation
Model Baselines
Model Tuning and Optimization
Model Review and governance
Automated Model retraining
Model Deployment and monitoring
Model Inference and Serving
Model Resource Management Techniques
Model Analysis
High-Performance Modeling

Model selection and evaluation

Cross-validation
Hyper-parameters Tuning
Performance Metrics
Validation curves

Applied Machine Learning Projects (40)

Applied Machine Learning projects repo

53 Implemented Projects

Take only these courses —

Complete Data Scientist:

Link to the course : https://bit.ly/3wiIo8u

Run data pipelines efficiently to extract, transform, and load data.
Design and conduct experiments to uncover valuable insights and drive data-based decision making.
Build powerful recommendation systems that personalize user experiences and increase engagement.
Deploy solutions to the cloud, enabling scalable and accessible data applications.
Master the essential skills needed to excel in the field of data science.

Complete Data Engineering:

Link to the course : https://bit.ly/3A9oVs5

Learn the art of designing effective data models that ensure data integrity and efficient storage.
Construct data warehouses and data lakes to enable centralized and organized data storage.
Automate data pipelines to streamline data processing and ensure timely and accurate data availability.
Gain expertise in handling and working with massive datasets efficiently.
Become a proficient data engineer equipped with in-demand skills for building robust data infrastructures.

Complete Machine Learning Engineer:

Link to the course : https://bit.ly/3Tir8ub

Acquire advanced machine learning techniques and algorithms to solve complex problems.
Develop skills in packaging and deploying machine learning models to production environments.
Master the art of model evaluation and selection to ensure optimal performance.
Learn to implement cutting-edge algorithms and architectures for superior machine learning results.
Equip yourself with the skills required to excel as a machine learning engineer.

Complete Natural Language Processing:

Link to the course : https://bit.ly/3T7J8qY

Build models that analyze and interpret human language, enabling sentiment analysis and machine translation.
Gain hands-on experience working with real data, developing practical NLP applications.
Uncover hidden patterns and extract valuable insights from textual data.
Understand the complexities of language and apply NLP techniques to solve challenging problems.
Unlock the power of language through the application of natural language processing.

Complete Deep Learning:

Link to the course : https://bit.ly/3T5ppIo

Master the implementation of Neural Networks using the powerful PyTorch framework.
Dive deep into the world of deep learning and understand its applications in various domains.
Gain hands-on experience in developing solutions for image recognition, natural language understanding, and more.
Learn about different architectures and techniques for building robust deep learning models.
Become proficient in utilizing deep learning to tackle complex problems and drive innovation.

Complete Data Product Manager:

Link to the course : https://bit.ly/3QGUtwi

Leverage the power of data to build products that deliver personalized and impactful experiences.
Lead the development of data-driven products that position businesses ahead of the competition.
Gain a deep understanding of user behavior and preferences through data analysis.
Develop strategies to optimize product performance and drive business growth.
Become a data product manager who can harness data's potential to create successful products.

Find complete Post here - Best Resources for Data Science and Machine Learning (full list)

Read about System Design 101 : Distributed Message Queue

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Projects Videos —

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