A news report published in October in The Economic Times said, “Start-ups witness 108% growth in funding in India in 2018.” The news report further mentioned that Artificial Intelligence was among those domains which witnessed the fastest adoption among industry sectors. Currently, there are about 400 start-ups working on AI and machine learning domains. About $150 million dollars is invested in India’s AI sector by private players alone and the number has been growing since 2016. Though there has been growth, India lags far behind countries like the US and China in terms of investment. With a copious pool of STEM talent and with a growing population of youngsters, India will be banking on AI for its economic growth and improvement in the quality of life of its citizens.

There are several start-ups that are based in cities such as Bengaluru, New Delhi, Mumbai and Hyderabad which work on artificial intelligence principles to serve consumers better. Their product range varies from multi-lingual chatbots to online shopping assistance and automated consumer data analysis

THE ROAD AHEAD

The National Strategy for Artificial Intelligence which was put together by the government of India through NITI Aayog sets the roadmap on how to develop AI in the country. The report points out how AI will help the country grow, what are the strengths and what are the challenges on the way. The government has identified a few areas where it thinks AI will play a crucial role as far as India is concerned

Capital and qualified manpower are the two main pillars that are required for the establishment and growth of any sector. India is home to a large talent pool of Science, Technology, Engineering and Math graduates. Companies such as Google, Intel and Microsoft have been offering short term training programs to computer program developers which help them upskill in the area of AI programming. On the other hand AICTE, the government body which governs and regulates professional education in India, recently added AI, IoT, Machine Learning and few other subjects as mandatory subjects in its curriculum of B.Tech programs. Changes in curriculum and content are further expected in the days to come.

Investment towards AI from private players has been increasing in India ($44 million in 2016 to $77 million in 2017). The start-ups have been working towards developing various AI-based products and services. With conglomerates having a lion’s share in India’s market, there is huge scope for AI-based enterprise solutions in the country. The increasing demand for products and services can attract more investment towards R&D in AI sector

there have been a lot of new trends in the AI sector not only in India but in the World overall

I have been reading many blogs and news articles and found this which shows an interesting few Trends in Artificial Intelligence and Machine Learning to Look for which I am sure you will find interesting!

if you wish to learn new insight into machine learning, you can learn AI and machine learning easily on the internet with some courses like these Machine Learning and Artificial Intelligence eBook for Newbies which provide tutorials online!

so talking about machine learning in India….

Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.

Machine Learning is currently one of the hottest topics in IT.. Technologies such as digital, big data, Artificial Intelligence, automation, and machine learning are increasingly shaping the future of work and jobs. is a specific set of techniques that enable machines to learn from data, and make predictions. …

Machine Learning Applications

Machine Learning in Education

Teachers can use Machine Learning to check how much of lessons students are able to consume, how they are coping with the lessons taught and whether they are finding it too much to consume. Of course, this allows the teachers to help their students grasp the lessons. Also, prevent the at-risk students from falling behind or even worst, dropping out.

Machine Learning in Search Engine

Search engines rely on Machine Learning to improve their services is no secret today. Implementing these Google has introduced some amazing services. Such as voice recognition, image search and many more. How they come up with more interesting features is what time will tell us.

Machine Learning in Digital Marketing

This is where Machine Learning can help significantly. Machine Learning allows a more relevant personalization. Thus, companies can interact and engage with the customer. Sophisticated segmentation focus on the appropriate customer at the right time. Also, with the right message. Companies have information which can be leveraged to learn their behavior.

Nova uses Machine Learning to write sales emails that are personalized one. It knows which emails performed better in past and accordingly suggests changes to the sales emails.

Machine Learning in Healthcare

This application seems to remain a hot topic for the last three years. Several promising start-ups of this industry as they are gearing up their effort with a focus on healthcare. These include Nervanasys (acquired by Intel), Ayasdi, Sentient, Digital Reasoning System among others.

Computer vision is the most significant contributors in the field of Machine Learning. which uses deep learning. It’s an active healthcare application for ML Microsoft’s InnerEye initiative that started in 2010 and is currently working on an image diagnostic tool.

If you are interested to learn Machine learning, better to learn via online resources.. I can also recommend some courses

Best Machine Learning Online Course that will surely get you started is:

Machine Learning for absolute beginners

You’ll go from beginner to high-level and your instructor will build each algorithm with you step by step on screen.

By the end of the course, you will have trained machine learning algorithms