The Complete Collection of Data Science Projects

Machine Learning

Machine learning is a hot topic in data science, and you will learn about the classification, regression, and clustering projects to solve business problems. It will help you understand the tabular dataset, data processing, training on algorithms, and model validation. 

• Music Genre Classification: Tutorial
• Credit Card Fraud Detection: Tutorial
• Flight Price Prediction: Tutorial | Code Source

Deep Learning

You will learn more advanced machine learning algorithms, neural networks, and data processing techniques. Deep learning is a huge subject, and to master it, you need to learn its applications in computer vision, NLP, forecasting, automatic speech recognition, generative art, and reinforcement learning. 

• Reinforcement Learning: Tutorial
• Gender and Age Detection with OpenCV: Tutorial
• Deep Learning for Time Series Forecasting: Tutorial

Computer Vision

In computer vision, you learn to process image data and train the model for various computer vision tasks such as image classification, generation, segmentation, and object detection. 

• Automatic colorization: Code Source
• One Shot Face Stylization: Code Source
• Image Segmentation: Tutorial

Natural Language Processing (NLP)

You will learn to understand language through images, text, and audio. Due to the introduction of large language models and transformers NLP has seen multiple applications in the real world. It is used for translation, question and answers, text summarization, text classification, text generation, and conversational AI. 

• Machine Translation Yorùbá to English: Tutorial | Code Source
• BERT Text Classifier on Tensor Processing Unit: Tutorial
• Automatic Speech Recognition: Tutorial | Code Source

Data Engineering

Design, validate, and deploy data pipelines for data science projects. You will learn everything about the data engineering process. You will also learn how these modern tools integrate to provide seamless data streams. It will introduce you to ETL, data modeling, orchestration, analytics, and serving tools. 

• Design, Development, and Deployment of a simple Data Pipeline: Tutorial | Code Source
• Uber Expenses Tracking: Tutorial | Code Source
• Data Compression and Data Decompression Pipeline: Tutorial | Code Source

MLOps

It is the production side of machine learning where engineers test, retrain, validate, and server inference in production. You will learn about ml pipeline tools, experiment and artifact tracking, storing and versioning data and models, cloud computing, REST API, and web applications. You will learn to create an end-to-end machine learning system. 

• MNIST MLOps Learning: Code Source
• NLP MLops Project With DagsHub: Tutorial | Code Source
• Machine Learning, Pipelines, Deployment, and MLOps: Tutorial

 Programming

If you are new to data science, the programming projects will help you get used to syntax, debugging, and learning new tools. Python, R, and Julia are mostly used for data processing, data analysis, machine learning, and research projects.

Python

• Tic-Tac-Toe: Tutorial | Code source
• QR Encoder & Decoder:  Tutorial
• Photo Manipulation: Tutorial | Code source

R

• Exploratory Data Analysis: Tutorial
• Tweet Analysis: Tutorial
• R Machine Learning: Tutorial

Julia

• Compressing Image: Tutorial
• Caesar Ciphers: Tutorial
• Rock Paper Scissors: Tutorial | Code Source

Web Scraping

Web scraping is a core part of data engineering and data science, where you collect new data from multiple websites to build a data set for data analysis or machine learning tasks. In general, it is used to create real-time data systems.

• Scraping Instagram: Tutorial
• Scrape a Job Portal: Tutorial
• Scrape Stock Prices: Tutorial

Data Analytics

The analytics project will teach you new tools for data cleaning, processing, and visualization. You will learn to understand data and create a report with valuable insights. 

• Analysis of American Universities: Tutorial | Code Source
• Data Cleaning Youtube Video Statistics: Tutorial
• World Tourism Analysis: Code Source

SQL

SQL is the most used tool for creating, managing, and streaming database systems. In most cases, you have run a few SQL scripts for analytical tasks, but integrating them into your project is hard to imagine. The list of projects will teach you how the scripts are used to create databases, store and retrieve the data, and how they are integrated with other tools. 

• Library Management System: Code Source
• Online Retail Application Database: Code Source
• Hospital Management System: Code Source

Business Intelligence

Learn to create interactive dashboards and analytical reports using BI tools. You will learn how small modules join together to create a dashboard and what value it brings to the business. 

• Construction Management: Code Source
• Customer Support Case: Code Source
• Wine Production in the United States: Code Source

Time Series

Learn to understand, process, and visualize time series data. You will learn to create anomaly detection systems, forecasting, and visualize multiple graphs for comparison. Time series is a whole new world within data science, so it will be quite valuable to add one of the projects to your portfolio. 

• Anomaly Detection: Tutorial
• Rainfall Prediction: Tutorial
• Superstore Sales: Tutorial | Code Source

This is the 5th edition in the collection series, check out:

1. The Complete Collection of Data Science Cheat Sheets – Part 1 and Part 2
2. The Complete Collection of Data Repositories – Part 1 and Part 2
3. The Complete Collection of Data Science Books – Part 1 and Part 2
4. The Complete Collection of Data Science Interviews – Part 1 and Part 2

 https://t.me/ai_machinelearning_big_data

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