How Apple, Amazon, Facebook and Google use Machine Learning in 2024
See how 4 technology companies use 10 different machine learning algorithms in 2024. And how you can apply these algorithms to your own business
Discover how tech giants like Amazon, Google, Facebook, and Apple are revolutionizing their businesses with machine learning. In this video, we explore the innovative ways these companies leverage algorithms like Decision Trees, Support Vector Machines, and Principal Component Analysis to optimize packaging, improve speech recognition, and support small businesses during the pandemic.
Learn how Amazon uses Gradient Boosting to supercharge Alexa’s conversational skills, how Facebook applies Logistic Regression to identify businesses at risk, and how Google utilizes Linear Regression for speaker adaptation in speech recognition systems. We also delve into Apple’s use of PCA for natural language processing and Amazon’s application of Random Forests for anomaly detection in streaming data.
By the end of this video, you’ll have a deeper understanding of how machine learning is driving innovation and solving complex real-world problems across industries. Stay ahead of the curve and unlock the potential of AI for your business.
For more mind-blowing content on the latest advances in machine learning and AI, subscribe to our channel and visit the research websites mentioned in the video:
Amazon Science: https://www.amazon.science/
Google AI Research: https://research.google/
Facebook (Meta) Research: https://research.facebook.com/
Apple Machine Learning Journal: https://machinelearning.apple.com/
Netflix Machine Learning: https://research.netflix.com/
0:00 Introduction
1:05 Amazon’s Use of Decision Trees for Packaging Optimization
2:10 Google and Facebook’s Use of Support Vector Machines (SVMs)
3:15 Amazon’s Application of Gradient Boosting for Alexa’s Conversational Skills
4:20 Facebook’s Use of Logistic Regression in the State of Small Business Survey
5:25 Amazon’s Use of K-Nearest Neighbors (KNN) for Regulatory Compliance
6:30 Apple’s Application of Principal Component Analysis (PCA) in Natural Language Processing
7:35 Amazon’s Use of t-SNE for Domain Adaptation in Neural Networks
8:40 Amazon’s Application of Random Forests for Anomaly Detection
9:45 Amazon’s Use of Naïve Bayes for Product Catalog Enhancement
10:50 Google’s Application of Linear Regression for Speaker Adaptation in Speech Recognition
12:00 Conclusion
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