Machine Learning with Python Hands-On Real-World Projects
Published 9/2026
Created by ZeroCostEdu Org
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 10 Lectures ( 5h 18m ) | Size: 1.8 GB
Learn Machine Learning with Python, NumPy, Pandas, Scikit-Learn, TensorFlow, Deep Learning, and real-world projects.
What you’ll learn
Build complete Machine Learning projects using Python and real-world datasets.
Perform data preprocessing, visualization, feature engineering, and model evaluation.
Train and evaluate regression and classification models using Scikit-learn.
Create a professional Machine Learning project portfolio for internships and jobs.
Requirements
Basic knowledge of Python programming is recommended.
Description
Welcome toMachine Learning with Python: Hands-On Real-World Projects, a practical course designed to help you learn machine learning by building real applications instead of only studying theory.
This course starts with the foundations of machine learning and gradually introduces essential Python libraries including NumPy, Pandas, Matplotlib, and Scikit-Learn. You will understand how to prepare datasets, clean and visualize data, engineer features, train machine learning models, evaluate performance, and improve accuracy.
As you progress, you will implement supervised and unsupervised learning algorithms such as Linear Regression, Logistic Regression, Decision Trees, Random Forest, Support Vector Machines, K-Nearest Neighbors, Naive Bayes, K-Means Clustering, and Principal Component Analysis. You will also learn the fundamentals of neural networks and deep learning using TensorFlow and Keras.
The course focuses on practical implementation. Every major topic is accompanied by hands-on coding exercises and real-world projects that reinforce the concepts you learn.
By the end of this course, you will have built multiple machine learning applications, created a professional project portfolio, and gained the confidence to solve real data science problems.
What you’ll learn
Python for Machine Learning
NumPy and Pandas
Data Cleaning and Preprocessing
Data Visualization
Feature Engineering
Regression Algorithms
Classification Algorithms
Clustering
Dimensionality Reduction
Model Evaluation
Hyperparameter Tuning
TensorFlow and Keras Basics
Deep Learning Fundamentals
Real-world Machine Learning Projects
Deploying Machine Learning Models
Who this course is for
Anyone who prefers learning through real-world projects rather than theory.
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