Course Outline
Introduction to Applied Machine Learning
- Distinctions between statistical learning and Machine Learning
- Cycles of iteration and evaluation
- Understanding the Bias-Variance trade-off
Supervised Learning and Unsupervised Learning
- Machine Learning languages, types, and practical examples
- Comparing Supervised and Unsupervised Learning
Supervised Learning
- Decision Trees
- Random Forests
- Evaluating models
Machine Learning with Python
- Selecting appropriate libraries
- Utilizing supplementary tools
Regression
- Linear regression
- Generalizations and handling nonlinearity
- Practical exercises
Classification
- Refresher on Bayesian principles
- Naive Bayes
- Logistic regression
- K-Nearest Neighbors
- Practical exercises
Cross-validation and Resampling
- Different approaches to cross-validation
- Bootstrap methods
- Practical exercises
Unsupervised Learning
- K-means clustering
- Case examples
- Challenges in unsupervised learning and methods beyond K-means
Neural Networks
- Understanding layers and nodes
- Python libraries for neural networks
- Implementation using scikit-learn
- Implementation using PyBrain
- Deep Learning concepts
Requirements
You should possess a solid understanding of the Python programming language. While not mandatory, a foundational grasp of statistics and linear algebra is highly recommended.
Testimonials (7)
Interesting knowledge
Gabriel - MINDEF
Course - Machine Learning with Python – 4 Days
The trainer was a practitioner with a lot of experience and had a very good knowledge of the material.
Witold Iwaniec - City of Calgary
Course - Machine Learning with Python – 4 Days
The trainer because he could handle almost every subject and situation.
Florin Babes - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days
The manner in which the trainer explained the concepts, his positive and welcoming attitude and the real-world examples provided for each exercise.
Ovidiu Calita - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days
Very good training session with nice documentation and exercises and Kristian did it like a professional he is.
Adrian Boulescu - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days
I like that he is very skilled and has lots of knowledge in his domain.
dan dumitriu - eMAG IT RESEARCH SRL
Course - Machine Learning with Python – 4 Days
rich documentation and many resources as course support, as well as resources for the post-course learning process
