Technology has become a mandatory element for all kinds of businesses across the globe. Machine Learning is a branch of Artificial Intelligence and learns from algorithms based on the database and derives answers and correlations from them. Be it automated cars, chatbots, smart cities and speech recognition, Machine Learning is everywhere around us.
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Types Of Machine Learning
- Supervised Learning
In this type of model, the algorithm learns on a labelled data set and generates predictions for new data response.
Supervised Learning can be of two types:
Classification Algorithm
A computer programme, when trained on a training dataset, categorizes the data in different class labels. There are types of Classification Algorithm such as Naive Bayes Classifier, Logistic Regression, Support Vector Machine and Random Forest Classification.
Regression Algorithm
Regression Algorithm is used to predict continuous values such as price, salary and marks etc. It finds the mapping function to map input variables(x) to the constant output variable (y). There are various types of Regression Algorithm such as Simple Linear Regression, Decision Tree Regression, Polynomer Regression and Multiple Linear Regression.
2. Unsupervised Learning
In this type of model, the algorithm learns on an unlabeled dataset and tries to extract features and co-occurrence. There are various types of Unsupervised Learning such as Association, Autoencoders, Neural Networks and Anomaly Detection.
3. Reinforcement Learning
In this type of model, the Machine Learning model learns to perform actions and analyze the reactions. To maximize the positive response in a particular situation, Reinforcement Learning takes appropriate action.
Real-World Applications Of Machine Learning
- Face recognition in smartphones
- Stock market trading
- Medical diagnosis
- Fraud detection
- Self-driving cars
- Machine Learning in agriculture
- Speech recognition feature in smartphones
- Weather prediction
- OTT platforms’ recommendation system
- Chatbot
Career Options For Machine Learning
Data Scientist
To become a Data Scientist, you must have a good knowledge of Machine Learning algorithms, statistics and a firm hold on Python language. The prominent role of a Data Scientist is to discover valuable information through the process of analyzing, modeling and inspecting the unstructured and raw data.
Designer In Human-Centered Machine Learning
The primary role of a designer who works in creating a human-centred Machine Learning is to develop systems that can do the task of processing information and analyzing patterns out of it. This type of system creates a smart user experience, like in the case of the Netflix recommendation system. Designers who can work with Machine Learning algorithms are also involved in making software for the banking sector, which can go through the vast number of financial transactions and determine which ones are fraudulent in nature.
Software Engineer
The primary skill of a Software Engineer is writing codes so as to develop algorithms. Good knowledge of Machine Learning enables you to write different software programmes for various purposes, including network distribution and operating systems.
Machine Learning as a field is growing tremendously as more and more industries are hiring Machine Learning experts. If you are thinking of making a career in Machine Learning, you can check out the courses offered by Teksands. They offer courses such as Online Courses on Data Analytics in India, Online Courses on Data Analytics in India, and Machine Learning Online Training in India.
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