Top 7 Machine Learning Frameworks of 2020

Machine Learning is an artificial intelligence subset that focusses on developing applications that enable machines to self-learn. The ultimate purpose of machine learning is to enable machines to work automatically without any human intervention.

What’s an ML framework?

Coding ML algorithms require a very high level of coding expertise. ML frameworks simplify the process of creating algorithms. An ML framework can be any interface, tool, library, or platform that helps you easily build ML models without having to build intensive algorithms. The ML framework that an engineer decides to use for a particular application depends on whether the application needs to analyse text, image, or data units.

A framework can help you make optimal use of the data to build ML applications and models to:

  • Detect faces
  • Manipulate images
  • Predict routine behaviours
  • Offer recommendations based on search and buying history
  • Generate articles on a subject

Top 7 Machine Learning Frameworks of 2020

The most popular Machine Learning frameworks of 2020 are:


PyTorch is developed by Facebook’s AI Research (FAIR). This ML framework follows a traditional object-oriented programming approach, which makes it highly customizable. It can be used in active development. PyTorch runs on the GPU as well as the CPU. It manages classification, neural networks and regression.


Scikit-learn is used to run ML model sketches quickly to evaluate their performances. This Python package ML framework takes care of tasks such as SVM, linear regression, K-Nearest neighbour, random forest regressions, and decision tree regressions. It can also be used along with the confusion matrix model analysis tool.

Spark ML

The Spark ML framework is written in Java or Scala. It is a complicated framework that can be used to run complex large matrix multiplication tables. However, it requires a distributed architecture as it needs huge memory capacities to run the large volumes of data. Spark ML framework is compatible with Spark SQL data frames.


TensorFlow is one of the most popular machine learning frameworks that focuses on statistical and mathematical modelling. It is an open source project developed by Google Brain. This framework is basically a complete ML research and development tool. Multiple data pipelines can be setup using TensorFlow. Also, the model can be transformed by customizing the layers and the models. The best thing about TensorFlow is that it can be run on multiple systems while still ensuring the privacy of the user on each system.


Torch, released in 2002, is one of the earliest and the easiest of ML frameworks. It is written using Lua coding language and comes with a LuaRocks packaging manager. The interface has only numbers and tables, which makes it very easy to understand and use. The basic element of Torch is a tensor. It also has a Command Line Interface (CLI) that provides help with indentation and inline help.


Huggingface is one of the newer machine learning frameworks. This library offers a solid base for ML researchers. It adapts complicated tools like the GPT-2 to allow you to easily work on ML tools on your computer system.


This neural network library is designed on top of TensorFlow. It can also be built on top of R, Microsoft Cognitive ToolKit (CNTK), Theano, and PlaidML. Keras simplifies ML coding with its all-in-one models. It also lets you use the same code for a CPU and a GPU.

Enrol in Machine Learning Course offered by Corpnce

You will find plenty of machine learning certification courses offered by many training centres in Bangalore. However, before you enrol in a machine learning course, you need to check the reputation of the institute. Also, you need to check if the institute offers hands-on training on the tools and frameworks.

Learn the popular machine learning frameworks, tools, and concepts by enrolling in the Machine Learning Course in Bangalore offered by Corpnce. We are one of the leading machine learning training institutes in Bangalore. Our training program is based on projects and practical applications. During the training, you will gain expertise in:

  • Scikit-learn
  • PyTorch
  • Python
  • Plotly
  • Jupter
  • Tableau
  • Matplotlib
  • Seaborn
  • Pandas
  • Numpy

Our project-based curriculum focusses on practical learning of the tools and technologies. So, you get to work on the machine learning frameworks in real time. Also, the training is led by industry experts who come with nearly a decade of industry experience. We also offer placement opportunities for aspirants who take up machine learning training in Bangalore with us.

Corpnce can help you get in-depth training on the ML frameworks, tools, and technologies. We can help you carve your career in this emerging domain. Contact us to enrol in our machine learning training course in Bangalore