Machine learning is one of the fastest-growing technologies that has made lives easier with its ability to imitate human learning. It is a part of artificial intelligence that helps analyse data, build models and make forecasts. Machine learning’s popularity has spread across industries making it an integral part of most. With its ever-growing demand, professionals and students alike, seek a data science and machine learning course to build and secure a successful career in the field.
Machine learning models are extremely useful in today's technologically driven world. Knowledge of machine learning tools will help professionals arrange data, improve and discover new data models and create algorithms. A data science and machine learning course also allows professionals to learn data mining.
Read on to learn about the popular machine learning tools a data scientist must know about.
Machine learning tools
The following are the most popular and useful ML tools:
It is one of the most extensively used open-source machine learning tools for developing deep learning models. Its popularity is because of a dynamic library, tools and resources that help deal with large amounts of data. It allows data scientists to create machine learning applications and build effective data models.
TensorFlow has the following features:
- Efficiently create and train data models
- TensorFlow.js allows users to effectively run existing models
- Possesses the advantage of distributed computing
- It can create neural networks
- Equipped with the facility of immediate iteration and constant debugging
- Training and deployment of the model in the cloud is easier
Fighters is an open-source machine learning tool with its foundation in the Torch library. This tool benefits machine learning with Python and C++. It allows users to have a better and more interactive interface that can be used to develop various applications.
The following are the main characteristics of Pytorch:
- The Autograde module is used to build neural networks
- It offers great flexibility and speed, which are important for researchers and data scientists
- It is well integrated with cloud platforms
- It has a dynamic computational graph which is unique in this library
- It has a hybrid front end and permits the random change of network behaviour without any lag
Google Cloud ML Engine
Google Cloud ML Engine provides training datasets making it easier to deal with huge amounts of data. This machine learning tool is the best choice where a company wants faster results and building models while dealing with data. The services of this tool permit the creation of ML models with any size and type of data.
Google Cloud ML engine has the following features:
- Provides training to build ML models, deep learning models, etc.
- Training and prediction can be used simultaneously or in a combined way
- It is highly suitable for locating clouds in a satellite image
- The library is equipped in dealing with complex models
Amazon Machine Learning (AML)
AML is exclusively developed by Amazon and provides a ton of machine learning tools. It is a cloud-based application that can build effective machine learning applications and make forecasts. It is dynamic and can integrate data from various sources
The major characteristics of AML are enumerated as follows:
- It provides wizards and multiple visualisation tools
- It helps to identify data patterns and build mathematical data models
- It supports regression, binary and multi-class classification
- It allows users to make predictions for data models in bulk using different APIs
Accord.net is an open-source machine learning tool that is specially used for scientific computing. This tool is highly used because it has image-processing features and audio libraries otherwise absent in many other tools. Another exclusive feature that this tool has is its ability to deal with statistical and mathematical learning.
Accord.net’s features are:
- It is equipped with more than 38 kernel functions
- It consists of a lot of statistical distribution, classified as a parametric and non-parametric approximation
- It is highly useful for signal processing, computer audition and vision
- It includes numerous hypothesis tests for analysing better results
Shogun is one of the oldest open-source machine learning libraries. This tool is written in C++ and supports a variety of interfaces. The objective of Shogun is to provide solutions for regression and classification problems.
The main features of Shogun are listed below:
- It permits the use of precalculated kernels
- It is equipped with the ability of multiple kernel functionality
- It makes it very easy to process large data sets
- It allows users to develop algorithms in a variety of programming languages
Machine learning is an inseparable part of the corporate world, and a knowledge of machine learning tools is one of the required qualities for becoming a successful data scientist. The IIT data science course is an advanced module that will teach you everything you need to know about the best machine learning tools in the market.
If you are a tech enthusiast and want to become a data scientist, then register for the Certificate Program in Data Science and Machine Learning by IIT Roorkee and Imarticus. This course is your one-stop destination for getting all the insights on machine learning tools.