This course provides a comprehensive introduction to machine learning using Python, focusing on key concepts, algorithms, and tools. You’ll explore …
Course Description
This course provides a comprehensive introduction to machine learning using Python, focusing on key concepts, algorithms, and tools. You'll explore supervised and unsupervised learning, model evaluation, and practical implementations through real-world datasets. Designed for beginners and intermediate learners, this course equips you with the skills to build, train, and optimize machine learning models using Python libraries like Scikit-learn and TensorFlow.
Learning Outcomes:
- Understand the fundamentals of machine learning concepts and algorithms.
- Implement supervised and unsupervised learning techniques.
- Use Python libraries such as Scikit-learn and TensorFlow.
- Evaluate machine learning models using performance metrics.
- Preprocess and analyze real-world datasets.
- Apply feature selection and dimensionality reduction techniques.
- Build and optimize machine learning models.
Course Content
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- Introduction to types of ML algorithm 00:02:00
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- Importing a dataset in python 00:02:00
- Resolving Missing Values 00:06:00
- Managing Category Variables 00:04:00
- Training and Testing Datasets 00:07:00
- Normalizing Variables 00:02:00
- Normalizing Variables – Python Code 00:03:00
- Summary 00:01:00
- Simple Linear Regression – How it works? 00:04:00
- Simple Linear Regreesion – Python Implementation 00:07:00
- Multiple Linear Regression – How it works? 00:01:00
- Multiple Linear Regression – Python Implementation 00:09:00
- Decision Trees – How it works? 00:05:00
- Random Forest – How it works? 00:03:00
- Decision Trees and Random Forest – Python Implementation 00:04:00
Original price was: £425.00.£25.00Current price is: £25.00. ex Vat
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Includes
- 46 hours on-demand video
- Full lifetime access
- Certificate of Completion