Artificial Intelligence
Intermediate
Online
Machine Learning with Python
A comprehensive machine learning course covering supervised and unsupervised learning, model evaluation, and deployment using scikit-learn and TensorFlow.
10 weeks
6 lessons
1 enrolled
0★ (0 reviews)
What You Will Learn
- Understand core ML algorithms
- Build regression and classification models
- Apply scikit-learn and TensorFlow
- Evaluate and tune models with cross-validation
- Handle real-world datasets with pandas
- Deploy ML models as REST APIs
Requirements
- Basic Python programming
- High school mathematics (algebra & statistics)
- Familiarity with Jupyter notebooks helpful
Syllabus
Week 1-2: Data Preprocessing & EDA Week 3-4: Linear & Logistic Regression Week 5-6: Decision Trees & Ensembles Week 7-8: Neural Networks with TensorFlow Week 9-10: Model Deployment & Capstone Project
1.
Data Preprocessing with Pandas
45 min
2.
Linear Regression from Scratch
40 min
3.
Classification with Logistic Regression
50 min
4.
Neural Networks with TensorFlow
60 min
5.
Introduction to Machine Learning
Free Preview
20 min
6.
Computer Vision Basics
Free Preview
30 min
Sarah Chen
PhD in Computer Science (MIT). Research focus on Deep Learning, NLP, and Computer Vision. 8 years teaching.
1 Courses
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