Course Outline
Introduction to Applied Machine Learning
- Distinguishing between statistical learning and Machine learning
- Processes of iteration and evaluation
- The Bias-Variance trade-off
Supervised Learning and Unsupervised Learning
- Overview of Machine Learning languages, types, and examples
- Contrasting Supervised and Unsupervised Learning
Supervised Learning
- Decision Trees
- Random Forests
- Evaluating model performance
Machine Learning with Python
- Selecting appropriate libraries
- Utilizing add-on tools
Regression
- Linear regression
- Handling generalizations and nonlinearity
- Practical exercises
Classification
- Refresher on Bayesian concepts
- Naive Bayes
- Logistic regression
- K-Nearest neighbors
- Practical exercises
Cross-validation and Resampling
- Strategies for cross-validation
- Bootstrap methods
- Practical exercises
Unsupervised Learning
- K-means clustering
- Applied examples
- Navigating the challenges of unsupervised learning and techniques beyond K-means
Neural networks
- Understanding layers and nodes
- Exploring Python neural network libraries
- Implementing solutions with scikit-learn
- Implementing solutions with PyBrain
- Introduction to Deep Learning
Requirements
Proficiency in the Python programming language is required. Basic familiarity with 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 5200 € + 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
