Machine Learning (ML) is emerging as one of sought after professional fields today. ML has become a part of various aspects of our everyday life. We don’t realize it but it has penetrated into our lives in various —be it Alexa or Siri, recommendations in Facebook/Instagram,
Gmail spam filters, traffic congestion predictions, customer support chatbots, and much more. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% from 2019 to 2025, reaching up to an estimated evaluation of USD 96.7 billion by the end of 2025.
What is Machine Learning
While shopping online, have you noticed how the system gives you recommendations for the product similar to your choice of product? Or noticed something like “the person who bought this product also bought this”? Have you ever wondered how are doing this? How are they able to deep dive to the extent to know your choices? Well, that’s Machine Learning.
The Concept of Machine Learning allows the machine to learn from experience and examples. They are able to do that without being programmed. So, in this case, instead of the code written by you, the data is fed to the generic algorithm, and the machine builds the logic on the basis of given data. Machine Learning is a subset of AI (Artificial Intelligence) which focuses on learning from experience and making predictions based on its experience.
What does it do
ML enables the computers to make data-driven decisions instead of being programmed for carrying out a certain task. The algorithms/programs are designed to learn and improve over the period of time being exposed to new data.
What are different types of Machine Learning
(i) What is Supervised Learning?
Supervised Learning is the one, where it can be considered that the learning is guided by a teacher. Here, the datasetacts as a teacher and has a role to train the machine or the model. Once trained, the model starts making prediction or decision as and when new data is provided to it.
(ii) What is Unsupervised Learning?
It is a self-sufficient kind of learning where the model learns through observation and by finding structures in the data. Once the model is provided with a dataset, it automatically finds relationships and patterns in the dataset through the creation of clusters in it. It cannot label the clusters. For instance, it cannot say this a group of onions or potatoes, but it will separate all the onions from potatoes.
If we presented images of Onions, Potatoes and Tomatoes to the model, based on some patterns and relationships it creates clusters and divides the dataset into clusters and adds new data to the created clusters.
(iii) What is Reinforcement Learning?
Based on hit and trial, the agent interacts with the environment and finds out the best outcome. The agent is penalized or rewarded with a point for any corrections or a wrong answer. The model trains itself on the basis of positive reward points. And once trained it is all set to predict the new data introduced to it.
Careers in Machine Learning:
Healthcare, Defence, Financial Services, Marketing and Security services are some of the key areas using machine learning as one of the tools to manage the business and understand customer buying pattern. The utility and reliability of Machine Learning open avenues for multiple career options for the experts in the field of Machine Learning.
Global salary trend and trend across the country:
The average salary of Machine learning professionals goes between 10 Lakhs to 15 lakhs in the big cities like Mumbai, Bangalore, Hyderabad,NCR, Pune as published in ‘salary reports’ in 2018.
As you can see there are ample of opportunities in this field, this is the time to upskill and brush up your skills in Machine Learning. Prepare yourself for the jobs of new world order by getting certified and working on real-life capstone projects to take advantage of Machine Learning career opportunities that come your way.
ADYPU Online has a curated Post Graduate Program in Machine Learning that will make you proficient in techniques like Supervised Learning, Unsupervised Learning, and Natural Language Processing. It includes hands-on training on the latest developments and technical approaches in AI (Artificial Intelligence) & Machine Learning such as Deep Learning, Reinforcement Learning and Graphical Models.
ADYPU also offers M. Tech programs in Artificial Intelligence & Machine Learning, Blockchain, Full Stack Development, Automotive Product Engineering, Digital Manufacturing, Bioengineering, Cybersecurity, MBA in Advanced Program in Business Intelligence and Data Analytics, MBA in Advanced HR Practices, and LLM in Corporate Law, Constitutional Law, and Cyber Law and Cybercrime Investigation. For enquiries and admissions, get in touch with us now.