Here are some interesting everyday examples around us where machines are learning and doing amazing jobs from detecting skin cancer to sorting cucumbers, to detecting escalators in need of repair, machine learning has granted computer systems entirely new abilities. E-mail spam recognition spell checks even the YouTube video recommendation is implemented using machine learning.
Machine learning software is deeply embedded into the tech industry and is vital to most businesses. The global market size for machine learning is expected to reach a value of 117.19 billion by 2027 and who knows where it'll be after that. Some applications of machine learning are listed here.
[ Figure: Applications of Machine Learning (Edited by me on PowerPoint)]
Explanation:
In healthcare, where Diagnostics are predicted for doctors, review the sentiment analysis that the tech giants are doing on social media.
In the finance sector, another interesting application of machine learning for fraud detection.
In the e-commerce sector, machine learning is used to predict customer churn while booking the gap you must have encountered surge pricing often where it says the Farrow field trip has been updated.
In transportation, an interesting machine learning model is used by global taxi giant “uber” and others where they have differential pricing in real-time based on demand the number of cars available in case of bad weather or rush hour, etc.
• Speech recognition
• Voice recognition
• Automated and self-driving Google car
• Smart Homes
• Smart Cities
• Smart Agriculture
• Learning Associations
• Medical Diagnosis
• Classification Processes
• Statistical Arbitrage etc.
Summary
In a nutshell, Machine Learning amazingly integrates things in the field of artificial technology. Although it has some shocking effects when you think about it. But these machine learning applications are just one of the many ways in which this technology can improve our lives.
I am also thankful to the management of SIZ for providing such a great platform where we can show our talent and skills.
Thank you for sharing your thoughts about machine learning and it's applications with us.
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