Table of Contents
What You’ll Learn
Gain a solid understanding of Python programming, including syntax, data structures, and control flow.
Explore the core principles and algorithms of machine learning, such as supervised and unsupervised learning.
Learn techniques for cleaning, preparing, and transforming data for machine learning models.
Discover methods for creating new features or selecting relevant features for model building.
About Course
How does Machine Learning Work
Types of Machine Learning
Supervised Learning & Examples
Unsupervised Learning & Examples
Reinforcement Learning & Examples
Examples of AI
Deep Learning & Examples
Jupyter & Installation
Machine Learning Tutorial & Algorithms
Demo of Iris Dataset
Linear Regression & Value of R2
Statistics and Probability Concepts-
Category of Data for Machine Learning
Qualitative data and Quantitative data in machine learning
Information gain & Entropy and Confusion Matrix
Types of event and Probability of Distribution
How to Import Datasets in Jupyter
Data Analysis
Train & Test Data
Logistic Regression Curve
Decision Tree
Class project 1
Class project 2
Description
Are you eager to dive into the exciting world of machine learning and harness the power of Python? This comprehensive course is designed to guide you from a beginner to a proficient machine learning practitioner.
Key Learning Objectives:
Master Python Fundamentals: Gain a solid understanding of Python programming, essential for machine learning.
Explore Machine Learning Concepts: Learn the core principles and algorithms of machine learning, including supervised and unsupervised learning.
Work with Real-World Datasets: Practice data cleaning, preprocessing, and feature engineering using real-world datasets.
Build Predictive Models: Develop various machine learning models, such as linear regression, logistic regression, decision trees, random forests, and neural networks.
Evaluate Model Performance: Learn to assess model accuracy, precision, recall, and other metrics.
Apply Machine Learning in Practice: Discover real-world applications of machine learning in fields like finance, healthcare, and marketing.
Course Highlights:
Hands-On Projects: Engage in practical exercises and projects to reinforce your learning.
Step-by-Step Guidance: Follow clear explanations and coding examples.
Real-World Examples: Explore real-world use cases of machine learning.
Expert Instruction: Learn from experienced machine learning professionals.
Lifetime Access: Enjoy unlimited access to course materials.
This Course is For:
Beginners in machine learning who want to learn Python.
Data analysts or scientists looking to enhance their skills.
Professionals seeking to apply machine learning to their work.
Beginners in machine learning who want to learn the fundamentals using Python.
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Who Can Learn
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