Udemy – Build 25 Real World Machine Learning Project In 2022

Udemy – Build 25 Real World Machine Learning Project In 2022
English | Tutorial | Size: 10.14 GB

Learn To Build Machine Learning Project Practically From Scratch

Studying Machine Learning opens a world of opportunities to develop cutting edge applications in various areas, such as cybersecurity, image recognition, medicine, and face recognition.

Machine Learning is no longer just a niche subfield of computer science but technology giants have been using it for years – Machine learning algorithms power Walmart product recommendations, surge pricing at Uber, fraud detection at top financial institutions, content that Twitter, LinkedIn, Facebook and Instagram display on social media feeds or Google Maps. Machine learning products are being used daily, perhaps without realizing it. The future of machine learning is already here, it’s just that machine learning career is exploding now because of smart algorithms being used everywhere from email to mobile apps to marketing campaigns. If you are in search of the most in-demand and most-exciting career domains, gearing up yourself with machine learning skills is a good move now.

With several machine learning companies on the verge of hiring skilled ML engineers, it is becoming the brain behind business intelligence. Netflix announced prize worth $1 million to the first individual who could enhance the accuracy of its recommendation ML algorithm by 10%. This is a clear evidence on how significant even a slight enhancement is in the accuracy of recommendation machine learning algorithms to improve the profitability of Netflix. Every customer- centric organization is looking to adopt machine learning technology and is the next big thing paving opportunities for IT professionals. Machine learning algorithms have become the darlings of business and consumers so if you want to put yourselves somewhere in the upper echelon of software engineers then this is the best time to learn ML.
Who this course is for:

Beginners in machine learning

1DL
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