Course Outline
Introduction to Applied Machine Learning
- Distinguishing between statistical learning and machine learning
- Cycles of iteration and evaluation
- The Bias-Variance trade-off
Supervised and Unsupervised Learning
- Overview of Machine Learning languages, types, and examples
- 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
- Handling generalizations and nonlinearity
- Practical Exercises
Classification
- Review of Bayesian concepts
- Naive Bayes
- Logistic regression
- K-Nearest Neighbors
- Practical Exercises
Cross-validation and Resampling
- Different cross-validation strategies
- Bootstrapping techniques
- Practical Exercises
Unsupervised Learning
- K-means clustering
- Real-world examples
- Addressing challenges in unsupervised learning beyond K-means
Neural Networks
- Understanding layers and nodes
- Python libraries for neural networks
- Implementation with scikit-learn
- Implementation with PyBrain
- Introduction to Deep Learning
Requirements
A solid understanding of Python programming is required. Additionally, a foundational knowledge of statistics and linear algebra is recommended.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 6400 € + VAT*
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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
