This project consolidates resources, notebooks, and projects for learning data science and machine learning. The content is curated from various courses on Udemy, designed to help you build a strong foundation in data science concepts, techniques, and tools.
This repository serves as a comprehensive guide for anyone looking to get started with data science or enhance their existing skills. The materials included here cover a wide range of data science topics, with practical exercises and projects to reinforce each concept.
The materials and projects in this repository are based on the following Udemy courses:
- Learn Python Programming Masterclass
- Python for Machine Learning & Data Science Masterclass
- Complete Data Science,Machine Learning,DL,NLP Bootcamp
- Complete Tensorflow 2 and Keras Deep Learning Bootcamp
- PyTorch for Deep Learning with Python Bootcamp
- Python for Data Science: Core programming skills, data manipulation with Pandas, and data visualization.
- Data Preprocessing: Data cleaning, handling missing values, feature scaling, and encoding.
- Exploratory Data Analysis (EDA): Techniques to uncover data patterns and insights.
- Machine Learning Algorithms: Implementing linear regression, decision trees, clustering, and more.
- Natural Language Processing (NLP): Text processing, sentiment analysis, and language modeling basics.
- Deep Learning: Fundamentals of neural networks, introduction to Pytorch, and applications.
- Model Evaluation and Selection: Methods to assess and choose optimal models.
- Docker for Data Science: Containerization basics, setting up environments, and deploying ML models.