A Beginner’s Guide for Machine Learning: A Roadmap to Intelligent Machine

Machine learning is undoubtedly the biggest topic of discussion in the digital world right now. In layman’s term, we define machine learning as the computer programs which learn by itself (through experiences) instead of any hardcoded rules. This is one of the major advantages of ML over AI. As Machine Learning involves learning from various different experiences and then using those experiences to predict the possible/correct outcomes.
Example: Suppose we need to create an application that recognizes a flower name sunflower. For that, we need to write a huge amount of rules and code to identify/detect it, especially various features of the flower to detect. Here the problem is that if a flower is present with a different color, size or shape we are not able to write the code beforehand (well in advance). Thus, we have to use machine learning to solve this issue.
To solve any Machine Learning Problem there are 4 steps that need to be followed:

1. Collect Data
2. Select Model
3. Train Model
4. Test the Model

Few examples of applications areas in Machine learning but not limited:

Giants like Google, Microsoft, Uber, Amazon, Facebook, Instagram, Apple constantly use such learning algorithms to gain valuable insights from data, recognize new trends and thus use them to increase their customer base as well as profits. The value of machine learning technology has been recognized by companies not only in the technology sector but across several industries that deal with huge volumes of data.

Healthcare:
Machine learning is becoming the fastest growing trend in the healthcare sector. Things are gone away when one needs to take any medical insurance simply by just medical test and some few documentation works. Time has come now, that if someone needs to buy insurance then he needs to wear a smart device (wristband type) for around one month. That device will keep all the track records of your day to day activity like how many times or hours you are doing exercise, blood pressure, how many times your heart beats in one minute, how many times you are taking fast food, you are taking any medication or not and so on. Hence, it will provide real-time patient information. Doctors and medical experts can use this information to analyze the health condition of an individual, draw a pattern from the patient history, and predict the occurrence of any ailments in the near future. Aloha Technology can help your enterprise for adapting Machine Learning

E-commerce/Social Media:
Top Companies like Amazon, Facebook, flipcart are hopefully using machine learning technology to analyze & observe the purchase/order history of their customers and make personalized & relevant product recommendations for their next purchase/order. Like in Facebook, it will give you friends suggestion (people you may know) and some pages which you might have liked or viewed earlier. Aloha Technology can help your E-Commerce website to adapt Machine learning.

Personal Assistant:
Personalized Web browsers, personalized movie-based recommendation system, Mood-based music players recommendation by providing lot of sample inputs and through experiences to train the model.

Intelligent Robots:
Lots of research have done in the field of robotics based on ML/DL algorithms and formed like IBM Watson, KIRIBO, Emotion based robot, Sophia, CHATBOTS (though Chatbots have been around for some time, they have evolved significantly. From command–based chatbots which could answer pre-defined limited set of questions and required manual help for complex ones to train, to AI chatbots that became smarter with time through machine learning, chatbots have witnessed an impressive change), SIRI, CORTONA (Cloud-based virtual assistant), are the few names which have been made to do the things. As part of machine learning trends, personalization of search results by using AI-powered analytics is going to be the next big leap in business.

Financial Sector:
The technology is also used to identify opportunities for investments and trade. It will also lower the risk of the market & helps to prepare better in order to prevent fraud/s. Soon, companies that bank upon AI and machine learning will be in a better position to anticipate risks, predict unplanned expenses, and do so much more to run lean in competitive markers. Although not every function can be automated, AI can be counted upon to make analytics more precise and efficient when compared to the manual method of running analytics. All these are possible as the working on the Internet is growing sharply, which lead to an increase in volumes of data gathering.