AI, ML, DL and DS

 

These are the buzz words of the day which offer lucrative career options. No more talk about electronics, computer or IT but trending shift of the technology is on to the artificial intelligence, Machine Learning and the Deep Learning and the Data Science. In this article I wish to bring the key differences and the tools available for development in these areas.

1.      Artificial Intelligence

Main role of AI is to give human intelligence to machines. The field of AI is concerned with the development of intelligent machines that can think and act like humans and can mimic human cognitive functions like learning and problem-solving. Examples could be Robots,  Self-driving cars,

AI deals with the various  issues like Reasoning and Problem Solving, Knowledge representation, Planning, Learning, Natural Language Processing (NLP), Perception, Motion and Manipulation, Social Intelligence, General Intelligence

2.      Machine Learning

Machine Learning makes use of huge amount of data for training the maching and thus giving it the ability to learn. It makes use of algorithms and statistical models to perform a task without needing explicit instructions.

There are three types of learning here:

 

Machine Learning often deals with the following issues:

Collecting data, Filtering data, Analyzing data, Training algorithms, Testing algorithms, Using algorithms for future predictions

Some  examples of Machine Learning are virtual personal assistants, refined search engine results, image recognition, and product recommendations.

3.      Deep Learning

Deep Learning make use of neural networks inspired by the human brain. It is not task-specific rather is an approach to Machine Learning  that focuses on learning data representations algorithms. Deep Learning is used for like Natural Language Processing (NLP), bioinformatics, drug discovery and toxicology etc.

4.      Data Science

Data Science is used in business development, it works by extracting insights from data by using scientific methods and algorithms. It uses Machine Learning with Big Data analytics and cloud computing to solve the real world problems. Various  phases of data science are – Discovery, Data preparation, Model planning, Model building, Communicating results, Operationalizing

5.      MATLAB Tools

MATLAB offers number of tools for these emerging fields for the researchers. You can interactively explore your data, select features, and train, compare, and assess models by using the Classification Learner and Regression Learner apps.

Using Classification Learner app you can explore supervised machine learning using various classifiers. You can explore your data, select features, specify validation schemes, train models, and assess results. You can perform automated training to search for the best classification model type, including decision trees, discriminant analysis, support vector machines, logistic regression, nearest neighbours, naive Bayes, kernel approximation, ensemble, and neural network classification.

With Regression Learner apps you can perform automated training to search for the best regression model type, including linear regression models, regression trees, Gaussian process regression models, support vector machines, kernel approximation models, ensembles of regression trees, and neural network regression models

Conclusion:

The AI&ML, and AI&DSAI&DS are called emerging field and offer lucrative jobs to candidates who have B.Tech degree. In addition to the degree advanced learners must explore MATLAB as it offers number of tools to work in these emerging fields.

Dr. Ravinder Nath Rajotiya, HOD ECE