A DEEP DIVE INTO
Deep-dive into google's machine learning models and how it relies more on logic than data
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What you'll learn
Understanding machine learning models
Improving data analysis and decision-making
How Google uses logic in machine learning
Implementing machine learning in real-world scenarios
3 Top Key Ideas (95 total)
Google’s main aim is to organise the world’s information and make it accessible and useful to everyone.
This is where AI comes in. Google has mastered machine learning and made life easy with all its applications. It is continuously updating its platform and is one step ahead. Google applies AI to products and new domains and helps to develop tools to ensure that everyone can access AI.
Machine learning algorithms are trained with examples, where they learn from past experiences and analyse historical data. As it continues training, it can identify patterns to make predictions about the future.
Google takes advantage of machine learning algorithms and systematically apply them across all their products, such as search, ads, YouTube, or Play. Machine learning is already part of services like Gmail, Google Search and Google Maps.
When you start typing in the search box, it will anticipate what you’re looking for, then provide suggested search terms for the same based on past searches, trends, or from your present location.
For example, bus traffic delays. Google gets all the real-time data on bus locations and forecasts, and can now provide predictions so you don’t have to rely on bus schedules.
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