Algorythm™| Intro to Machine Learning

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A fundamental understanding of machine learning is crucial for professionals pursuing careers in data science, artificial intelligence, or similar domains. Machine learning enables the development of systems capable of learning from data and making informed predictions or decisions. By grasping essential concepts and techniques, individuals can apply these skills to various applications including natural language processing, computer vision, and recommendation systems.

Participants will gain the ability to assess the strengths and weaknesses of different machine learning models, enabling them to select the most suitable approach for their specific challenges.

Mastering the principles of machine learning will allow professionals to stay updated with advancements and innovations in this rapidly evolving field.

By the conclusion of the course, participants will be equipped to:

Comprehend fundamental concepts and terminology related to machine learning, which include supervised, unsupervised, and reinforcement learning, as well as classification, regression, and clustering.
Utilize relevant machine learning techniques to address practical issues
Implement and work with widely-used machine learning algorithms and frameworks
Critically analyze and interpret the outcomes and limitations of machine learning models
Investigate the ethical and social consequences of machine learning applications, focusing on aspects like fairness, privacy, and accountability.

Interactive Q&A sessions will cover the following models:

Supervised learning versus Unsupervised learning
Logistic regression
K-means clustering
Decision Trees
Boosting and Bagging algorithms
Time series analysis
Kernel SVM
Naive Bayes
Random Forest classifiers

WHO SHOULD ATTEND THIS COURSE?

(Non-technical) Entrepreneurs aiming to establish AI startups
Individuals transitioning from non-technical backgrounds
Students interested in exploring the AI landscape

Machine learning represents a thrilling and swiftly changing arena that provides numerous opportunities for both personal and professional development. Whether individuals seek to boost their career prospects, resolve real-world challenges, or explore their curiosity, participating in a machine learning course can facilitate their goals in harnessing this transformative technology.

Exciting opportunities lie ahead!

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Average annual income for entry-level machine learning engineers is approximately $96,000, ranging between $70,000 and $132,000 (US).

When

From: 25 December 2024, 19:00

To: 25 December 2024, 22:00

Where

. 00000 SP SAO PAULO BR

Algorythm™| Intro to Machine Learning

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When

Where

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