Top 10 Latest Applications of Machine Learning in Daily Life in 2020 by Technology Masters

This video "Top 10 Latest Applications of Machine Learning in Daily Life in 2020" by Technology Masters will explain some of the applications of Machine Learning which we come across in everyday life. Machine learning is starting to reshape how we live and it has become a part of our lives. We are already seeing how this technology is being implemented in a wide variety of industries. This latest ML (Machine Learning) technology is part of Artificial intelligence.

Las 10 aplicaciones más recientes del aprendizaje automático en la vida diaria en 2020

Top 10 der neuesten Anwendungen des maschinellen Lernens im täglichen Leben im Jahr 2020

Top 10 des dernières applications du Machine Learning dans la vie quotidienne en 2020

أفضل 10 تطبيقات للتعلم الآلي في الحياة اليومية في عام 2020

2020 میں روزانہ کی زندگی میں مشین لرننگ کے 10 تازہ ترین ایپلی کیشنز

2020年の日常生活における機械学習のトップ10最新アプリケーション

Топ 10 последних применений машинного обучения в повседневной жизни в 2020 году

2020 में दैनिक जीवन में मशीन लर्निंग के शीर्ष 10 नवीनतम अनुप्रयोग

2020年日常生活中机器学习的十大最新应用

Whether you realize it or not, machine learning is one of the most important technology trends, it underlies so many things we use today without even thinking about them. Speech recognition, Amazon and Netflix recommendations, fraud detection, and financial trading are just a few examples of machine learning commonly in use in today’s data-driven world. Now, lets deep dive into this video and see the top 10 applications of Machine Learning including:
-- Traffic Alerts
-- Social Media
-- Transportation and Commuting
-- Products Recommendations
-- Virtual Personal Assistants
-- Self Driving Cars
-- Dynamic Pricing
-- Online Video Streaming
-- Fraud Detection

Data Science is a set of techniques that enable computers to learn the desired behaviour from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. ML (machine learning) involves the application of different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. ML (machine learning) also involves the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.

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