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Top 10 AI Tools & Frameworks Every AI Engineer Needs To Know

AI tools in 2022 and 2023 are new-gen technology that can process code, solve problems independently, and clean data to improve business operations.

Artificial Intelligence is already a staple of the business world, and thousands of companies compete in today’s ever-changing tech landscape.

If you haven’t yet implemented tools for your AI solutions in your business, here is the list of the best Artificial Intelligence tools you can choose from if you are planning to implement end-to-end growth.

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Here is the infographic representation of top 10 AI tools and frameworks every AI engineer needs to know.

top 10 tools for AI


Scikit-Learn is one of the best Artificial Intelligence solutions in the machine learning community for automation processes. Some essential features that make Scikit Learn the top choice of developers include feature extraction, cross-validation, supervised learning algorithms, etc.

  • It runs on a single processor CPU and is built on SciPy.
  • The tool focuses on data modeling rather than manipulating it.
  • It includes a lot of calculations for projects like regular AI and data mining.
  • It is less suitable for complex calculations but can handle simple ones effectively.


TensorFlow is the most sought-after machine learning and deep learning library. It is a Python-friendly open-source framework that facilitates numerical computation to make future predictions.

  • It utilizes a multi-layered hub arrangement to rapidly set up, train, and send counterfeit neural systems.
  • It runs on CPU and GPU and is built on a deployable scale.
  • Applications made by TensorFlow can be run on Android, iOS, local machines, and the cloud.
  • Developers can easily create graphical visualization and construct neural networks using Tensorboard.


Theano stands apart from other conversational intelligence solutions as it exploits the PC’s GPU. The high speed of popular AI platforms makes them profitable for computationally complex undertakings and profound learning.

  • Theano is specifically designed to integrate with Python.
  • It is an AI-powered library that helps developers to develop, optimize, and launch code projects.
  • It is built with ML (Machine Learning models) capabilities to obtain actionable insights.
  • It can independently diagnose and solve bugs with little to no external support.


Caffe is another popular open-source AI system that has a Python interface. Due to its high processing power, which is more than 60 million images per day, Caffe is a popular Artificial Intelligence application for faster projects.

  • Caffe structure is a BSD-authorized C++ library with a Python interface.
  • The profound learning structure is popular for its high speed, quality, and articulation.
  • One of the best examples of the Caffe framework includes Google’s DeepDream.

Apache MxNet

Apache MxNet is an advanced Artificial Intelligence platform and framework adopted by Amazon. Its deep learning framework based on AWS allows for trading computation time for memory.

  • MxNet, an application created with scalability in mind, has easy-to-use support for multi-GPU.
  • With MxNet, you can quickly write custom layers in high-level languages.
  • TVM support is available, which will improve deployment support and run on new device types.


Keras is a high-level open-source framework that uses a neural network library. It is specially designed for the team looking for a user-friendly framework with a Python interface.

  • It runs seamlessly on CPU and GPU.
  • It is useful for fast prototyping that facilitates state-of-the-art experiment completion.
  • An AI framework like Keras is suitable for creating a functioning prototype.


The next comprehensive AI model built on Python is PyTorch, which is similar to TensorFlow. It is created by Facebook and is in relentless reception development.

  • It is suitable for projects that require faster development.
  • PyTorch can handle large and complex projects that TensorFlow cannot manage.
  • It is incredibly flexible and has rich APIs for the library extension.


Built on similar lines as TensorFlow, CNTK is a Microsoft Cognitive Toolkit. Anyone can try CNTK as it is under an open license. However, CNTK is challenging to deploy and requires special skills and expertise.

  • With CNTK, you can quickly combine model types like recurrent networks, convolution nets, and DNNs.
  • It has wider APIs like Java C, C++, Python, etc.
  • CNTK majorly focuses on creating deep learning neural networks.


One of the most robust and recent additions to Artificial Intelligence is AutoML. It can automate all the processes involved in articulating a real-world problem with the help of ML techniques.

  • Beginners can also use intelligent automation solutions to preprocess and clean data.
  • With AutoML, you can quickly perform data analysis to obtain real-time and data-driven results and optimize model hyperparameters.
  • It can accelerate ML research and help you save time and resources.


OpenNN, or Open Neural Networks, is a popular library for neural network simulation. The OpenNN library, written in C++, is essential to deep learning research.

  • OpenNN is an advanced technology that even experienced developers can use.
  • It features a Neural Designer that is suitable for advanced analytics.
  • The AI tool provides graphs and tables for data entry interpretation.

AI Tools

Integrate Top AI Tools To Grow Your Business 

Enterprises have realized the benefits of Artificial Intelligence in business, and around 37% of companies use AI tools in some form. Not only will the AI application integration power the company, but it will also improve business efficiency through data management.

Inferenz is a team of AI and ML experts who can help your business with AI-powered tools. The experts will analyze your business needs and ensure that you choose the right AI tools that fuel business growth with real-time insights.


  • Which are the best AI tools? 

Some of the best technologies available are MxNet, PyTorch, TensorFlow, OpenNN, etc.

  • What are AI tools and AI platforms? 

An Artificial Intelligence tool and platform allows developers to create intelligent business applications.

  • What are the three types of AI? 

Three AI types include Artificial narrow intelligence (ANI), Artificial general intelligence (AGI), and Artificial superintelligence (ASI).

  • Why are AI tools important? 

AI solutions are specifically designed to help enterprises to make better business decisions, improve speed and accuracy, boost core business processes, and so on.