Machine Learning Bootcamp Python, Projects & Deployment - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Machine Learning Bootcamp Python, Projects & Deployment (/Thread-Machine-Learning-Bootcamp-Python-Projects-Deployment)

Machine Learning Bootcamp Python, Projects & Deployment - OneDDL - 01-22-2026 Free Download Machine Learning Bootcamp Python, Projects & Deployment Published 1/2026 Created by Siddhardhan S MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 128 Lectures ( 66h 27m ) | Size: 37.3 GB Learn Python, Math, Machine Learning, Build Real-World Projects & Deploy ML Apps on AWS What you'll learn ✓ Build machine learning models using Python, covering classification, regression, and unsupervised learning. ✓ Understand the math behind machine learning, including linear algebra, statistics, probability, and calculus with clear intuition. ✓ Perform data collection, EDA, preprocessing, feature engineering, and model evaluation using real-world datasets. ✓ Apply cross-validation, hyperparameter tuning, and model selection to build reliable and optimized ML models. ✓ Convert ML notebooks into production-ready Python scripts and serve models using FastAPI and Streamlit. ✓ Deploy complete, end-to-end machine learning applications on AWS EC2 with real-world workflows. Requirements ● No prior Machine Learning experience is required. You will learn everything from scratch. ● No advanced math background is needed. All required math concepts are explained with intuition and examples. ● Basic computer skills and willingness to learn and practice are sufficient. ● A laptop or desktop with internet access (Windows, macOS, or Linux). ● No paid software required. All tools used are free and open-source. ● Some sections involve AWS deployment. An AWS account is helpful but optional. Description This is a complete, hands-on Machine Learning bootcamp designed to take you from Python basics to building and deploying real-world, production-ready ML applications. You will learn Machine Learning the right way - starting with Python and essential math foundations, working with real datasets, building models, evaluating them correctly, and finally deploying ML systems on AWS. Unlike theory-heavy courses, this bootcamp focuses on practical understanding, clean code, real projects, and real deployment workflows used in industry. What you will gain from this course • Strong Python programming skills for Machine Learning • Clear intuition for math behind ML including linear algebra, statistics, calculus, and probability • Hands-on experience with data collection, EDA, and preprocessing • Build and evaluate classification, regression, and unsupervised models • Proper model validation, cross-validation, and optimization techniques • Multiple real-world Machine Learning projects • Convert notebooks into clean, production-style Python scripts • Build ML APIs using FastAPI and UIs using Streamlit • Deploy complete ML applications on AWS EC2 • Work on production-grade capstone projects you can showcase in your portfolio Who this course is for • Beginners starting Machine Learning from scratch • Students preparing for ML or data science roles • Professionals transitioning into Machine Learning • Developers who want to build and deploy real ML applications No prior Machine Learning, Python or math background is required. Everything is explained step by step with intuition and hands-on examples. By the end of this bootcamp, you will not just understand Machine Learning - you will be able to build, deploy, and explain real ML systems with confidence. Who this course is for ■ Beginners who want to learn Machine Learning from scratch with Python and clear step-by-step guidance. ■ Students and freshers preparing for careers in Machine Learning, Data Science, or AI. ■ Working professionals looking to transition into Machine Learning or upskill with real-world projects. ■ Software developers who want to add Machine Learning and deployment skills to their toolkit. ■ Learners who want to build and deploy real, production-ready ML applications instead of just notebooks. Homepage [To see links please register or login] Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live [To see links please register or login] No Password - Links are Interchangeable