Day 17 of 30 days of Data Engineering Series with Projects

Aug 06, 2023

Welcome back peeps to Day 18 of Data Engineering Series with Projects!

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

Read about System Design 101 : Distributed Message Queue

Projects Videos —

Subscribe today!

Ignito Youtube Channel

Subscribe and Start today!!

Github : https://bit.ly/3jFzW01

Learn how to efficiently use Python Built-in Data Structures

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

53 Implemented Projects

Complete System Design with Implemented Case Studies and Code

Link to Repo

Description - This repository contains everything you need to become proficient in System Design .

60 days of Data Science and ML with project Series

Link to Repo

Description - This repository contains everything you need to become proficient in Data Science and Machine Learning .

Complete Data Structures and Algorithms and System Design Series

Link to Repo

Description - This repository contains everything you need to become proficient in Data Structures and Algorithms

Complete Data Engineering with Projects Series

Link to Repo

Description - This repository contains everything you need to become proficient in Data Engineering

Tech-Interview : Important Topics and Techniques

Link to Repo

Description - This repository contains everything you need to become tech interview Ready with most important tips and techniques.

ML/AI Research Papers Solved

Link to Repo

Description - This repository contains everything you need to become proficient in ML/AI Research and Research Papers .

Complete ML Ops With Projects Series

Link to Repo

Description - This repository contains everything you need to become proficient in MLOps

Complete Advanced SQL Series

Link to Repo

Description - This repository contains everything you need to become proficient in Advanced SQL

Time Series Analysis and Forecasting

Link to Repo

Description - This repository contains everything you need to become proficient in Time Series Analysis and Forecasting

Complete Pytorch with Projects Series

Link to Repo

Description - This repository contains everything you need to become proficient in PyTorch

Complete Scikit learn with projects

Link to Repo

Description - This repository contains everything you need to become proficient in Scikit learn

Part 1 of this can be found here - Link

What is Linkedin?
Important Features
Scaling Requirements — Capacity Estimation
Data Model — ER requirements
High Level Design
Basic Low Level Design
API Design
Complete Detailed Design
Complete Code

Design Whatspp

What is Whatsapp
Important Features
Scaling Requirements — Capacity Estimation
Data Model — ER requirements
High Level Design
Basic Low Level Design
API Design
Complete Detailed Design

What is Amazon Prime Video
Important Features
Scaling Requirements — Capacity Estimation
Data Model — ER requirements
High Level Design
Basic Low Level Design
API Design
Complete Detailed Design

What is BookMyShow?
Important Features
Scaling Requirements — Capacity Estimation
Data Model — ER requirements
High Level Design
Basic Low Level Design
API Design
Complete Detailed Design

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

Day 17 of 30 days of Data Engineering Series with Projects

Data Science using Python

Data Visualization

Statistics

Data Collection and Data Cleaning

Data Manipulation

Linear Algebra for Machine Learning

Supervised Learning

Classification Algorithms

Logistic Regression

Support Vector Machines and Decision Trees

Boosting and K-Means Clustering

Unsupervised Learning

Modeling

Model selection and evaluation

53 Implemented Projects

Things you must know in System Design -

Let us know what do you think…

Happy learning!

Discussion about this post