Course Outline
Introduction to Applied Machine Learning
- Distinctions between statistical learning and Machine Learning
- The process of iteration and evaluation
- The Bias-Variance trade-off
Supervised Learning and Unsupervised Learning
- Overview of Machine Learning languages, types, and use cases
- Contrasting Supervised and Unsupervised Learning
Supervised Learning
- Decision Trees
- Random Forests
- Assessing Model Performance
Machine Learning with Python
- Selecting appropriate libraries
- Utilizing add-on tools
Regression
- Linear regression
- Generalizations and handling nonlinearity
- Practical Exercises
Classification
- Refresher on Bayesian concepts
- Naive Bayes
- Logistic regression
- K-Nearest Neighbors
- Practical Exercises
Cross-validation and Resampling
- Different Cross-validation strategies
- Bootstrap techniques
- Practical Exercises
Unsupervised Learning
- K-means clustering
- Case Studies
- Challenges in unsupervised learning and techniques beyond K-means
Neural networks
- Understanding Layers and nodes
- Exploring Python neural network libraries
- Implementation with scikit-learn
- Implementation with PyBrain
- Introduction to Deep Learning
Requirements
You should possess a solid working knowledge of the Python programming language. Additionally, having a foundational understanding of statistics and linear algebra is strongly 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
