Machine Learning

Machine learning is a growing technology which enables computers to learn automatically from past data. Machine learning uses various algorithms for building mathematical models and making predictions using historical data or information.

Machine Learning is said as a subset of artificial intelligence that is mainly concerned with the development of algorithms which allow a computer to learn from the data and past experiences on their own. How does Machine Learning work?

A Machine Learning system learns from historical data, builds the prediction models, and whenever it receives new data, predicts the output for it. The accuracy of predicted output depends upon the amount of data, as the huge amount of data helps to build a better model which predicts the output more accurately.

Types of Machine Learning Supervised learning Supervised learning is a type of machine learning method in which we provide sample labeled data to the machine learning system in order to train it, and on that basis, it predicts the output. The system creates a model using labeled data to understand the datasets and learn about each data, once the training and processing are done then we test the model by providing a sample data to check whether it is predicting the exact output or not.

Supervised learning can be grouped further in two categories of algorithms: Regression Classification Important Deep Learning Algorithms Feed Forward Neural Network (FFNN) Convolutional Neural Network (CNN) Recurrent Neural Network (RNN) Long Short-Term Memory (LSTM) Autoencoders Generative Adversarial Network (GAN) Application Automation: Machine learning, which works entirely autonomously in any field without the need for any human intervention.

Healthcare industry: Healthcare was one of the first industry to use machine learning with image detection. Speech Recognition: Speech recognition is a process of converting voice instructions into text, and it is also known as "Speech to text", or "Computer speech recognition.“

Product recommendations: Machine learning is widely used by various e-commerce and entertainment companies such as Amazon, Netflix, etc., for product recommendation to the user. Self-driving cars: Machine learning plays a significant role in self-driving cars. Tesla, the most popular car manufacturing company is working on self-driving car.

Application Email Spam and Malware Filtering: We always receive an important mail in our inbox with the important symbol and spam emails in our spam box, and the technology behind this is Machine learning. Stock Market trading: Machine learning is widely used in stock market trading.

In the stock market, there is always a risk of up and downs in shares, so for this machine learning's long short term memory neural network is used for the prediction of stock market trends.

Medical Diagnosis: In medical science, machine learning is used for diseases diagnoses. Automatic Language Translation: Nowadays, if we visit a new place and we are not aware of the language then it is not a problem at all, as for this also machine learning helps us by converting the text into our known languages.

Google's GNMT (Google Neural Machine Translation) provide this feature, which is a Neural Machine Learning that translates the text into our familiar language, and it called as automatic translation