Difference Between Machine Learning, NLP, and Deep Learning.

Machine Learning :

Machine Learning or ML is a sub-field of Artificial intelligence (AI) that uses statistical techniques to solve large amounts of data without any human intervention. Machine Learning helps solve problems similar to how humans would but using large-scale data and automated processes. ML can assume a vital part in a wide scope of basic applications, for example, information mining, regular language handling, picture acknowledgment, and master frameworks. ML gives likely arrangements in this large number of areas and the sky is the limit from there and is set to be a mainstay of our future civilization.

Application:

1. Email Spam Prediction
2. Online Fraud Detection
3. Traffic Prediction
4. Recommendation System

Natural Language Processing (NLP):

Natural Language Processing is the ability of a computer program to understand human language as it is spoken. It investigates the use of computers to process or understand human languages for the purpose f performing useful. NLP is the relationship between computers and human language.

Some applications of NLP are:

1. Sentiment Analysis
2. Information Extraction
3. Information Retrieval
4. Chat Bot

Deep Learning:

Deep Learning is the subset of the field of machine learning based on Artificial neural networks that teach computers to learn by example. It is a function of artificial intelligence that imitates the human brain in processing data and creating patterns for decision-making uses. It is an AI function that mimics the human learning and thinking process to process data that is both unstructured and unlabeled.

Application:

1. Google Language translation
2. Alexa
3. Self-Driving Cars
4. Voice Synthesis
5. Facial Recognition