93 Days — 91 Data Science, Machine Learning and Deep Learning Projects
Get set go…
Welcome back peeps. Hope all’s well. We are starting a new project series 93 days ( that’s the no of days left to 2023) to build 91 projects — Data Science, Machine Learning and Deep Learning ( also some of them will be ML research projects).
For Advanced SQL Series —
Complete Data Structures and Algorithm Series
System Design Case Studies — In Depth
Design Instagram
Design Netflix
Design Reddit
Design Amazon
Design Messenger App
Design Twitter
Design URL Shortener
Design Dropbox
Design Youtube
Design API Rate Limiter
Design Web Crawler
Design Amazon Prime Video
Design Facebook’s Newsfeed
Design Yelp
Design Uber
Design Tinder
Design Tiktok
Design Whatsapp
Most Popular System Design Questions
Mega Compilation : Solved System Design Case studies
You can build these off office hours ( that’s what I’ll be doing) or over the weekends.
Let’s dive in!
Objective —
The main aim of this project series is to build in depth understanding of the important concepts of Data Science, Machine Learning and Deep Learning from a practical perspective and get hands on practice by building NLP projects (without falling in the rabbit hole of too much theory)
Github for the code —
This is where the project code would be uploaded.
Projects on youtube —
Projects Videos —
All the projects, data structures, SQL, algorithms, system design, Data Science and ML , Data Analytics, Data Engineering, , Implemented Data Science and ML projects, Implemented Data Engineering Projects, Implemented Deep Learning Projects, Implemented Machine Learning Ops Projects, Implemented Time Series Analysis and Forecasting Projects, Implemented Applied Machine Learning Projects, Implemented Tensorflow and Keras Projects, Implemented PyTorch Projects, Implemented Scikit Learn Projects, Implemented Big Data Projects, Implemented Cloud Machine Learning Projects, Implemented Neural Networks Projects, Implemented OpenCV Projects,Complete ML Research Papers Summarized, Implemented Data Analytics projects, Implemented Data Visualization Projects, Implemented Data Mining Projects, Implemented Natural Leaning Processing Projects, MLOps and Deep Learning, Applied Machine Learning with Projects Series, PyTorch with Projects Series, Tensorflow and Keras with Projects Series, Scikit Learn Series with Projects, Time Series Analysis and Forecasting with Projects Series, ML System Design Case Studies Series videos will be published on our youtube channel ( just launched).
Subscribe today!
Pre-requisite to all the Data series
60 days of Data Science and ML Series ( Day 1–60 covered)
Github repo for 60 days of Data Science and ML with projects series —
Project Topics —
This will span from Python, Data Science, ML, NLP and Deep Learning, Research Projects as follows —
Python — Completed
Data- Completed
Data preprocessing ( Collecting, Labeling and Validating data)
Advanced SQL — Completed
Set Theory Operations, Stored Procedures and CASE statements in SQL
Subqueries, Group by, order by and Having clauses in SQL and Analytical Functions
BigQuery Basics, SELECT, FROM, WHERE and Date and Extract in BigQuery
Common Expression Table, UNNEST Clause, SQL vs NoSQL Databases
Data Analytics — Completed
Data Analytics basics and kickstart of Data analytics with projects series
Data Analytics Ecosystem — Data Life Cycle, Data Analysis complete process ( most important things)
Projects
Data Science and ML Projects
Modeling
Model Baselines
Model Review and governance
Automated Model retraining
Model Deployment and monitoring
Model Inference and Serving
Model Resource Management Techniques
Model Analysis
High-Performance Modeling
Developing
ML workflows
MLOps Logging and Documentation
MLOps Makefile
ML Lake
MLOps tools and Frameworks
Testing and Reproducibility
Versioning
Docker
Production
Continuous Integration
Continuous Delivery and Deployment
Monitoring and Logging
Feature Stores
MLOps architecture and Infrastructure Stack
Model Serving Patterns and Infrastructures
Relational Databases and SQL
RDBMS
Data Modeling
NoSQL Data bases and Map Reduce
Unstructured Data
Advanced ETL
Map-Reduce
Data Warehouses
Data API
Data Processing Techniques
Batch Processing : Apache Spark
Stream Processing — Spart Streaming
Build Data Pipelines
Target Databases
Big Data
Big data basics
HDFS in detail
Hadoop Yarn
Sqoop Hadoop
Hadoop Yarn
Hive
Pig
Hbase
WorkFlows
Airflow hands on project
Infrastructure
Docker
Kubernetes
Power BI
Neural Networks
Different types of neural networks
Linear Classifiers
Optimization
Gradient Descent
Backpropagation Algorithm
Regularization — L2 and dropout regularization
Batch normalization
Build a Neural Network With Pytorch
Build a neural network in TensorFlow
Train Neural Networks
Feedforward neural network
Popular Optimization Algorithms
Activation Functions
Strategies for reducing errors
Shallow Neural Networks
Convolutional Neural Networks
Convolution basics and CNN Architectures
Residual networks
Build a Convolutional Network
Batch Normalization and Dropout
Recurrent Neural Networks
Tensorflow
Tensorflow Playground
Custom Loss Functions
Custom Layers and Models
Callbacks
Distributed Training
Data Pipelines with TensorFlow Data Services
Performance
Autoencoders
Generative Learning
Generative Adversarial Networks
Generative Adversarial Networks Basics
Useful activation functions and Batch normalization
Transposed convolutions
Generator and Discriminator
Deep Convolutional Generative Adversarial Networks
Implement Generative Adversarial Networks
Attention and Transformers
Attention and Transformers Basics
Sequence to Sequence Models
Attention
Multi-Head Self-Attention
Building Blocks of Transformers
Encoder
Decoder
Parameters Sharing
Build a Transformer Encoder
Research Papers and Projects —
Data Science
Paper Focus —
Data Dimensionality reduction
Latent semantics
Social/databases Query and Search
Search and recommendation
Large-scale recommender and search systems
Prescriptive analytics and data visualization
Knowledge discovery
Machine Learning
Paper Focus → NLP and ( Bit of ) Computer Vision
Natural Language Processing —
Text Classification and Summarization
Question Answering
Sentence Level semantics and Argument Mining
Sentence Similarity
Speech Recognition
Neural Machine Translation
Document Summarization
Textual Inference
Computer Vision —
Augmented reality
Pattern recognition
Stochastic Models
That’s it for now. Oct 2022 is going to be exciting, so get ready to learn and build.
Let me know if you have questions in the comment section below. Subscribe/ Follow, Like/Clap and Stay Tuned!!
Join Us!
Day 2 : SQL Basics, Query Structure, Built In functions Conditions
Day 4 : Set Theory Operations, Stored Procedures and CASE statements in SQL
Day 6 : Subqueries, Group by, order by and Having clauses in SQL and Analytical Functions
Day 7 : Window Functions, Grouping Sets and Constraints in SQL
Day 8 : BigQuery Basics, SELECT, FROM, WHERE and Date and Extract in BigQuery
Day 9 : Common Expression Table, UNNEST Clause, SQL vs NoSQL Databases
Day 10 : Triggers, Pivot and Cursors in SQL
Day 14 : MySQL in Depth
Day 15 : PostgreSQL inDepth
Anyways, For Day 15 of 15 days of Advanced SQL, we will cover —
PostgreSQL inDepth
Github for Advanced SQL that you can follow —
All the projects, data structures, algorithms, system design, Data Science and ML, Data Engineering, MLOps and Deep Learning videos will be published on our youtube channel ( just launched).
Subscribe today!
System Design Case Studies — In Depth
Complete Data Structures and Algorithm Series
Github —
Some of the other best Series —
How to solve any System Design Question ( approach that you can take)?
30 days of Data Structures and Algorithms and System Design Simplified
Data Science and Machine Learning Research ( papers) Simplified **
100 days : Your Data Science and Machine Learning Degree Series with projects
Complete Data Visualization and Pre-processing Series with projects
Exceptional Github Repos — Part 1
Exceptional Github Repos — Part 2
Tech Newsletter —
If you are interested, you can join my newsletter through which I send tech interview tips, techniques, patterns, hacks — Software Development, ML, Data Science, Startups and Technology projects to more than 30K readers. You can subscribe to Tech Brew :
Keep learning and coding :)
For Python Projects —
For complete 60 days of Data Science and ML : Day 1 — Day 60 : Quick Recap of 60 days of Data Science and ML
For other projects, tune to —
Build Machine Learning Pipelines( With Code)
Recurrent Neural Network with Keras
Clustering Geolocation Data in Python using DBSCAN and K-Means
Facial Expression Recognition using Keras
Hyperparameter Tuning with Keras Tuner
Custom Layers in Keras
