Machine Learning Bootcamp

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Step 1

You choose the course

Empower your learning journey—You choose the course, we make it happen!

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Step 2

You choose when

All of our Halloween courses are held over a period of 2 hours at a rate EUR 100 per person, on a one-to-one basis. On the application form, we ask you to indicate the day and time which would suit you best. We will do our best to accomodate you.

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Step 3

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Halloween

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Delve into the expansive field of Machine Learning. This comprehensive course covers supervised learning (classification and regression), unsupervised learning (clustering and fuzzy clustering), reinforcement learning, computer vision (morphology, OCR, segmentation, detection), natural language processing (encoding, semantic analysis, chatbots), and the mathematical foundations of learning theory and machine learning.

Halloween

Machine Learning: Section 1 - Introduction to Machine Learning and Linear Regression

In this section, you'll explore the foundations of Machine Learning, starting with Linear Regression. Learn the concepts of simple and multiple linear regression, their Python implementations, and their industry relevance by predicting housing prices based on various factors.

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Halloween

Machine Learning: Section 2 - Linear Regression Assignment

Dive deeper into Linear Regression through assignments. Work on problem-solving, evaluation rubrics, and final submissions while building models to understand the factors and parameters used in linear regression.

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Halloween

Machine Learning: Section 3 - Logistic Regression

Progress to binary classification with Logistic Regression. Explore univariate and multivariate logistic regression, model building, evaluation, and industry applications by predicting telecom operator customer churn.

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Halloween

Machine Learning: Section 4 - Logistics Regression Assignment

Apply your knowledge through problem-solving and assignments related to Logistic Regression. Work on problem statements, evaluation rubrics, and final submissions while implementing machine learning concepts.

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Machine Learning: Section 5 - Unsupervised Learning: Clustering

Venture into unsupervised learning with Clustering. Learn about K-Means Clustering, Hierarchical Clustering, and other forms of clustering like K-Mode, K-Prototype, and DB Scan. Understand how to group elements into clusters without predefined labels.

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Halloween

Machine Learning: Section 6 - Clustering Assignment

Apply your newfound knowledge by working on problem statements, evaluation rubrics, and final submissions in the Clustering Assignment. Implement machine learning concepts related to clustering.

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