Course Outline
Foundations of Applied Machine Learning
- Distinctions between Statistical learning and Machine learning
- Processes of Iteration and evaluation
- The Bias-Variance trade-off
Paradigms of Supervised and Unsupervised Learning
- Machine Learning Languages, Types, and Examples
- Differences between Supervised and Unsupervised Learning
Supervised Learning Techniques
- Decision Trees
- Random Forests
- Model Evaluation
Implementing Machine Learning in Python
- Selecting appropriate libraries
- Essential Add-on tools
Regression Analysis
- Linear regression
- Generalizations and Nonlinearity
- Practical Exercises
Classification Methods
- Review of Bayesian principles
- Naive Bayes
- Logistic regression
- K-Nearest neighbors
- Practical Exercises
Cross-validation and Resampling Strategies
- Various Cross-validation approaches
- Bootstrap methods
- Practical Exercises
Unsupervised Learning Approaches
- K-means clustering
- Illustrative Examples
- Challenges in unsupervised learning and alternatives to K-means
Neural Networks
- Understanding Layers and nodes
- Python libraries for neural networks
- Implementation using scikit-learn
- Implementation using PyBrain
- Deep Learning concepts
Requirements
Proficiency in the Python programming language is required. Additionally, having a foundational understanding 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