Discover the fundamentals of machine learning. Learn to harness supervised and unsupervised learning techniques to build powerful, actionable models.
This three-day training enables participants to master the fundamental concepts of data preparation and the main algorithms used in machine learning. Covering supervised and unsupervised learning techniques, the course delves into data properties, variable selection, univariate statistics, feature engineering, as well as foundational algorithms such as linear and logistic regression, neural networks, and decision trees. By the end of the training, participants will be fully capable of building and understanding machine learning models, applying best practices in Python, and effectively interpreting results
Discover the fundamentals of machine learning. Learn to harness supervised and unsupervised learning techniques to build powerful, actionable models.
Prerequisites
None
Format
Three-days interactive workshop
Follow-up
Evaluation form & practical exercices
Group size
3 - 6 participants
Total Cost (group)
2.250 € HTVA per participant
Total Cost (individual)
2.550 € HTVA per participant
Objectives
This training begins with a solid foundation on data properties, feature selection, and univariate statistics for building an effective algorithm base. Participants then explore supervised and unsupervised learning, covering key algorithms such as linear regression, logistic regression, neural networks, and decision trees. Practical exercises in Python accompany each algorithm to deepen understanding. The final day is dedicated to advanced techniques, including dimensionality reduction (PCA) and ensemble methods such as random forest and XGBoost, ensuring participants are fully prepared to implement machine learning solutions
Key elements of the machine learning with python training :
This three-day training enables participants to master the fundamental concepts of data preparation and the main algorithms used in machine learning. Covering supervised and unsupervised learning techniques, the course delves into data properties, variable selection, univariate statistics, feature engineering, as well as foundational algorithms such as linear and logistic regression, neural networks, and decision trees. By the end of the training, participants will be fully capable of building and understanding machine learning models, applying best practices in Python, and effectively interpreting results
Our instructors are highly experienced in machine learning and possess strong expertise in Python development. With a focus on practical, hands-on applications, they guide participants through the complexities of building and fine-tuning machine learning models. All participants will have full access to course materials, including code examples, datasets, and step-by-step tutorials, ensuring a comprehensive learning experience.
20 & 21 February (fr)
Brussels (Delta)
J1 : Data Visualization
J2 : Data Modeling
1.500 €/Htva per participant
13 & 14 February (fr)
Brussels (Central)
Data Visualization
1.250 €/Htva per participant
At eaQbe, we transform your data into actionable insights. With a focus on efficiency, automation, and intelligent systems, we tailor our solutions to your business's unique needs, ensuring seamless integration and impactful results.
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