Top Machine Learning Frameworks

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Machine Learning is a trending technology used in almost every domain, such as security, healthcare, e-commerce, IT, and many more. It provides consistent solutions for vast data sets and makes things seamless. Many companies are adopting Machine Learning, but the challenging part is choosing the best suitable machine learning framework. Our experts have curated a list of the top five machine learning frameworks that help you get a better understanding of their features. 



What is Machine Learning?

Machine learning is a significant part of Artificial Intelligence that uses statistical methods and enables machines to enhance with experience. Machine Learning algorithms are designed to learn and improve from experience in identifying and adopting the data patterns to make data-driven predictions. These predictions play a significant role in making data-driven decisions and mitigating human errors. 

What are Machine Learning Frameworks?

The Machine Learning framework is an interface that allows developers and data scientists to build and deploy machine learning models much more quickly. It provides an end-to-end pipeline and simplifies machine learning algorithms. Let’s check out the top machine learning frameworks.


  1. Google’s TensorFlow

First on the list is Google’s Tensorflow, an open-source machine learning framework for computations used in data flow graphs. It includes a rich set of tools for classifications, programming, neural networks, and regression models. Tensorflow consists of a framework known as Tensorflow.js, which allows developers to integrate existing projects and build advanced ML models.


  1. Amazon Machine Learning

Second on the list is Amazon Machine Learning, which is a cloud-based robust framework that allows developers to build machine learning models quickly. It provides various data visualization tools used to create models without expertise in machine learning techniques. Amazon Machine Learning framework connects to storage and runs binary classification, regression, or multiclass categorization on the data.


  1. Scikit-Learn

Scikit-Learn is the most popular machine learning tool developed for python programming language and supports machine learning and deep learning classifiers to build ML models. It is designed for unsupervised learning calculations for AI assignments, such as relapse, order, and bunching.


  1. Pytorch

Next on the list is Pytorch, an open-source Machine Learning library with many features for optimizing algorithms. It is used in Natural Language Processing (NLP) and computer vision. Pytorch is a python-based framework used to develop neural network-based deep learning models. 


  1. H2O

Last on the list is H2O, an open-source ML framework used to solve complex organizational problems on data and allows users to derive insights. It integrates with other ML frameworks for fraud analysis, predictive modeling, advertising technology, customer intelligence, and insurance analytics.

How will InfosecTrain help?

InfosecTrain offers an instructor-led online certification training program on Machine Learning with Python. It helps you to achieve good knowledge of Machine Learning and develop machine learning algorithms using Python. If you want to enhance your career as a Data Scientist, check out the training program and enroll.

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