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Top 10 Artificial Intelligence Tools

Technological advancement has led to the tremendous growth of artificial intelligence tools. AI tools are now in high demand than ever before.

by Owl
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Artificial intelligence tools and Machine Learning are widely used in a large percentage of various industries.

So, what is Artificial Intelligence? It is the simulation of human intelligence processes by machines, especially computer systems. AI works by consuming a massive amount of training data, analyzing it for patterns and correlations, and using the patterns to make future predictions.

In this article, we’ll learn more about ten different artificial intelligence tools. So, let us jump right in.

1. Tensorflow

Tensorflow is a free, python-friendly open source library. It is an excellent AI tool that aids algorithmic computation while ensuring easier and accurate future predictions.

The tool uses a multi-layered centre to allow you to train, generate and send counterfeit systems with big data. It has a Tensorboard that helps developers in constructing neural networks and designing graphical visualization. You can run this tool on Android and iOS devices, the cloud, and the CPU.

2. Scikit Learn

Scikit Learn is one of the most popular machine libraries. This library uses Scientific Python that you have to install before you can start using the sci-kit-learn library. The tool runs on one processor CPU and focuses on modelling the data.

Scikit has the following features:

  • Ipython: this is a backup for interactive computing, and you can use it with a variety of programming languages.
  • SciPy: contains technical and scientific computing modules such as signal and image processing, integration, and linear algebra.
  • NumPy: this has an array of mathematical functions.
  • Pandas: you can use this library to analyze and manipulate data.
  • Matplotlib: this is a visualization and plotting library. You can create multiple graphical plots to visualize the machine learning models.

3. Cloud AI Platform

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Photo by Tara Winstead from Pexels

This AI is a cloud computing platform that provides artificial intelligence and machine learning services. With Cloud AI, you can easily create machine learning projects and use them in your company’s projects. In addition, the tool offers services such as text-to-speech translation, IVR robots, and voice bot creation.

When using Cloud AI for your business, you can utilize the ready-made models that google provides or customize your own that suits your needs.

4. MxNet

With MxNet, you can trade computing time for memory via a ‘forgetful backprop’ feature, which can be very handy for recurrent nets running on a long sequence. It has the following benefits:

  • It has direct support for multi-machine and GPU training.
  • It has excellent features for world-class languages.
  • A large corporation doesn’t directly govern; it is a positive feature for an open-source, community-developed framework.
  • It offers TVM support to allow it to run on new devices.

5. Apache MXNet

Amazon uses this AI as its learning framework on AWS. It has a friendly environment for an open-source framework as a big corporation does not own it. You can efficiently run this Artificial intelligent Intelligent tool on a variety of machines and GPUS. The tool also supports various APIs such as JavaScript, Perl, Go, and Python.

6. IBM Watson

IBM Watson has advanced AI capabilities. It has also developed specific AI using Waston to sectors like media, healthcare, financial services, etc. The tool has natural language processing (NLP) by Watson Natural Language Understanding (NLU).

Further, IBM Watson offers pre-built applications and other tools to allow users to create, run and monitor AI solutions for their companies. You can use the device in different departments such as customer service, financial operations, risk management, and IT operations.

Features of IBM Watson for app development:

  • It has a Watson Assistant that you can integrate to create AI-powered conversational interfaces into your app.
  • It has detailed documentation for its developer tools like SDKs
  • IBM Watson offers Watson Discovery, an AI-powered search technology that helps your app recover information stored in silos.
  • It has Natural Language Processing (NLP) capabilities known as Watson Natural Language Understanding.
  • It also has IBM Waston Speech to Text capabilities that you can use to create a Watson developer platform.

7. Theano

Theon is an open library designed by the LISA group of the University of Montreal, Quebec, Canada. The tool creates models of deep learning and simplifies them for fast usage in innovative work. It operates on Python 2.7 or 3.5, and you can consistently run it on CPUs and GPUs.

The ability of Theano to exploit GPU allows it to make information escalated counts compared to when it’s exected on the CPU only. The tool has a high speed to carry out complex computation and profound learning.

8. Cafe

Berkeley Vision and Learning Center (BVLC) and network donors designed caffe. It is made with high speed, articulation, and top quality—Google’s DeepDream is highly dependent on Caffe Framework. The tool is a C library and has an interface of Python.

With Caffe, you can process over 50 million photos in one day. The tool is widely used in areas like visions, research area projects, speech and multimedia.

9. Pytorch

PyTorch is a scientific package based on Python, and it utilizes the power of GPU (Graphics processing units). It offers an easy-to-use API, and it also provides a robust platform that offers dynamic computational graphs that you can change during the run time.

 

10. Keras

Kera was created by Francois Chollet ( an engineer at Google). It is an open-source neural network library programmed in Python language. You can run Kera on other libraries like Theano and Tensorflow to perform low-level computation.

The tool handles high-level API, and it compiles models with loss and optimizer functions. You can learn how to use Kera on their website.

Bottom line

The above top artificial intelligence tools help data scientists and engineers to solve real-life problems and makes the architecture system powerful and excellent. To gain a competitive edge, it would be best to strive to get certification in Artificial Intelligence. Build that successful career path today by learning and understanding Artificial Intelligence tools. It is believed that by 2022 Artificial Intelligence will have created 58 million new Artificial Intelligence jobs.

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