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10 Essential Machine Learning algorithms for 2025 in 17 minutes - A Visualisation & Intuition

Автор: Lucidate

Загружено: 2024-06-05

Просмотров: 911

Описание: A visualisation and intuition for the ten 10 most important Machine Learning Algorithms in less than 17 minutes.

Links to related playlists:

Machine Learning
   • Machine Learning  

Ensembles
   • Ensembles  

Machine Learning Shorts
   • Machine Learning Shorts  

Chapters:
Support Vector Machine (SVM) 1:02
Linear Regression: 2:45
Logistic Regression: 3:48
K-Nearest Neighbours (KNN): 5:11
Decision Trees: 6:43
Random Forests: 8:11
Gradient Boosting (AdaBoost): 9:41
Naive Bayes: 11:49
Principal Component Analysis (PCA): 13:01
t-Distributed Stochastic Neighbour Embedding (t-SNE): 14:21

In today's data-driven world, machine learning is no longer a luxury - it's a necessity. As more and more industries embrace AI and data science, understanding the key machine learning algorithms is becoming essential for professionals across fields. Whether you're a business leader looking to make better decisions, a product manager aiming to build smarter products, or a data analyst seeking to extract insights from complex datasets, mastering these algorithms is a game-changer.

But the impact goes beyond individual careers. Companies that effectively leverage machine learning are seeing significant economic benefits. According to a recent McKinsey report, AI will deliver an additional economic output of around $13 trillion by 2030, boosting global GDP by about 1.2% a year. This means that organisations investing in machine learning talent and technology are positioning themselves for a substantial competitive advantage.

Unlock the power of machine learning with this comprehensive overview of the 10 most important ML algorithms. In just 17 minutes, you'll gain a solid understanding of key techniques like Support Vector Machines (SVM), Linear Regression, Logistic Regression, K-Nearest Neighbors (KNN), Decision Trees, Random Forests, Gradient Boosting (AdaBoost), Naive Bayes, Principal Component Analysis (PCA), and t-Distributed Stochastic Neighbor Embedding (t-SNE).

Whether you're a business leader, product manager, data analyst, or professional looking to upskill in AI and data science, this video is your fast track to mastering the essential machine learning algorithms. Each algorithm is explained with clear visualizations and intuitive examples, making complex concepts easy to grasp.

As more industries adopt machine learning, understanding these key algorithms is becoming crucial for staying competitive. Companies that effectively leverage ML are seeing significant economic benefits, with AI predicted to deliver an additional $13 trillion in economic output by 2030. Investing in machine learning talent and technology now positions organizations for substantial gains in the coming years.

Don't miss out on this opportunity to boost your machine learning skills. Like this video, subscribe to our channel, and leave a comment letting us know which algorithm you found most valuable. For deeper dives into each technique, check out the links in the description below.

Upgrade your machine learning knowledge today and unlock the full potential of data-driven decision making!

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10 Essential Machine Learning algorithms for 2025 in 17 minutes - A Visualisation & Intuition

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