Machine Learning Bootcamp for Complete Beginners - Build Real Projects with Python

Publicado em: 22 Outubro 2025
no canal de: azamsharp

1,066

🎓 Machine Learning for Beginners – Build Real Projects with Python

Welcome to the Machine Learning for Beginners course! 🚀
In this hands-on course, you’ll learn the core concepts of machine learning and apply them to real-world datasets using Python, scikit-learn, NumPy, pandas, and Flask. Whether you’re new to data science or want to strengthen your ML fundamentals, this course will take you from theory to practical implementation step-by-step.

Python for Beginners - The Complete Course:
• Python for Beginners - The Complete Course...

💡 What You’ll Learn
By the end of this course, you’ll be able to:

Understand what machine learning is and how it’s applied across industries
Set up your ML environment using Miniconda and Google Colab
Work with essential Python ML libraries such as NumPy, pandas, scikit-learn, and Matplotlib
Build regression models to predict house and car prices
Apply Logistic Regression for classification problems like customer purchases and heart disease detection
Explore Decision Trees and Random Forests for powerful predictive modeling
Use KMeans Clustering and the Elbow Method for unsupervised learning tasks
Reduce dimensionality with Principal Component Analysis (PCA)
Deploy your trained ML model to the web using Flask and create a user-friendly interface

🏆 Who This Course Is For
Beginners curious about Machine Learning and AI
Developers wanting to add ML skills to their portfolio
Students preparing for data science or analytics roles
Professionals who want to automate predictions using data

🧠 Machine Learning – Welcome
02:04 – What is Machine Learning 📘
08:36 – What is Miniconda 💻
13:40 – Setting Up Environment Using Miniconda ⚙️
27:27 – Setting Up Environment Using Google Colab ☁️
33:10 – Machine Learning Tools and Packages 🧩

📈 Machine Learning – Linear Regression
38:11 – Understanding Linear Regression 📊
55:08 – Introduction to Linear Regression ✏️
1:05:54 – House Prices & One-Hot-Encoding 🏠
1:30:51 – Carvana Dataset and Car Prices 🚗

📊 Machine Learning – Logistic Regression
1:48:48 – Understanding Logistic Regression 📉
2:04:19 – Customer Sales (Purchase or Not) 🛒
2:24:28 – Heart Disease Dataset ❤️

🌳 Machine Learning – Trees
2:36:47 – Understanding Decision Trees 🌲
2:41:13 – Decision Trees in Action 🔍
2:58:07 – Understanding Random Forest 🌳
3:05:07 – Random Forest Classification 🌿

🧩 Machine Learning – Clustering
3:16:36 – Understanding KMeans 🔢
3:24:56 – Introduction to KMeans 🧠
3:50:21 – Understanding Elbow Method 📈

🔢 Machine Learning – PCA
4:01:46 – What is PCA? 🧮
4:08:40 – Using PCA with MNIST Dataset ✨

💻 Flask Project – House Prices Website
4:32:48 – What We Will Be Building 🏗️
4:34:08 – Training the Model 🧠
4:51:27 – Building the User Interface Using Flask 🌐

🔗 Continue Learning with AzamSharp School
Explore 180+ hours of in-depth courses, live workshops, and 1-on-1 coaching at AzamSharp School (azamsharp.school)
Master iOS, Swift, and Machine Learning development with real-world projects and expert guidance.

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