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Hands-On Python Machine Learning with Real World Projects

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Published 10/2024
Created by Sayman Creative Institute
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 13 Lectures ( 4h 8m ) | Size: 1.3 GB

Python Based Machine Learning Course with Practical Exercises and Case Studies

What you’ll learn
Applications of machine learning
Data manipulation and analysis
Building a predictive model to forecast sales
Essential Python libraries (NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn)

Requirements
No experience required

Description
Are you ready to unlock the power of machine learning with Python? This comprehensive course is designed to equip you with the essential skills to build predictive models that can solve real-world problems.From beginner to expert, we’ll guide you through the entire machine learning process, starting with the fundamentals of Python programming. You’ll learn how to:Prepare and clean data for analysisExplore different machine learning algorithms and their applicationsBuild and train predictive models using popular libraries like Scikit-learn and TensorFlowEvaluate model performance and refine your approachApply machine learning techniques to a variety of real-world problems, including:Regression: Predicting continuous values (e.g., house prices)Classification: Categorizing data (e.g., spam detection)Clustering: Grouping similar data points (e.g., customer segmentation)Neural networks and deep learning: Building complex models for tasks like image and natural language processingThroughout the course, you’ll work on hands-on projects that will help you solidify your understanding and develop practical skills. We’ll also provide you with real-world case studies to demonstrate how machine learning can be applied to solve business challenges.By the end of this course, you’ll be able to:Confidently use Python for machine learning tasksBuild and deploy predictive models that drive business valueStay up-to-date with the latest trends in machine learning


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