10 Best Tools for Building AI Algorithms in 2018

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Building AI Algorithms

The stage is set for AI developers to come up with life-changing algorithms by the start of 2018 through a host of tools. Making use of these tools, AI developers across the globe will be able to make progress in multiple fields that will completely change the way we look at technologies. You are all aware of the promising virtual assistants like Microsoft Cortana and Siri from Apple which have become a part of our daily life. All these are possible through the use of the right software along with a proven set of tools and technologies that will create enriching AI experiences.

If you are inquisitive to know about the best tools of 2018 that will help machine learners and AI developers produce top-notch AI algorithms, here they come.

1. Watson
Signing up with Watson can benefit developers in more ways than one. Being a robust AI supercomputer developed by IBM, a developer can make the most of its prominent and useful tools like image recognition, ability to strike a conversation and Natural Language Processing (NLP).

2. Keras
Looking to prototype an AI algorithm? Then Keras can become your best AI tool. Tagged as a neural network API, Keras is built exclusively to initiate swift experimentation along with another benefit. And that is to simplify the process of understanding User Experience. If you are a developer planning to make your first move into AI by 2018, then Keras can help you get started.

3. TensorFlow
If you are looking for an open source machine learning library that employs data flow graphs, then TensorFlow can be your top AI tool for the coming year. Loaded with a host of functionalities, you can effortlessly make use of TensorFlow to successfully deliver a number of projects. This tool can be banked upon majorly for its image recognition capabilities.

4. Jupyter
Independent of any programming language that you wish you to code in, Jupyter comes across as an open-source web application notebook. Capable of integrating a number of big data tools, Jupyter helps software development teams share live code documents, including visualizations, equations and narrative text.

A host of other uses of this tool are: numerical simulation, data transformation and cleaning along with statistical modeling and machine learning. Developed under a multi-purpose and interactive Python environment, this notebook is an AI tool that swiftly prototypes machine learning.

5. Scikit-learn
If you wish to perform the activities concerning analysis of data and data mining, you can check out the Scikit-learn tool that is built for Machine Leaning in Python. Tagged as an open-source and commercially usable code, Scikit-learn allows you to classify objects which are linked to the spheres of image recognition and detection of spam. Businesses can make the most of this AI tool to come up with customer segmentation and grouping of experimental results.

6. Sound and Voice Interfaces
Next in the list of AI tools for 2018 are voice interfaces like Google Home and Amazon Echo. These will be the upcoming and modern personal assistants that are being developed through NLP which will include the capabilities of AI bots. Locating stuff at home is now an instruction away. The all-new Amazon Echo is an example of a far-field technology tool that follows your instructions to perform activities desired by you; like turning on the heater or locating your smartphone.

The Upcoming AI Tools from Microsoft Azure
Microsoft Azure is a provider of AI-powered intelligent cloud services and introduces you to experience the next-generation applications. This is a completely-managed cloud service that facilitates the building, deployment and analysis of data through predictions. Offering a set of cognitive services, here are some of the tools enlisted under the head of its Cognitive Services Directory.

Some of Microsoft Azure’s Vision Based AI Tools are Computer Vision API, Emotion API, Face API and Custom Vision Service. All these tools can detect outdoor and indoor images through the utilization of cognitive features.

Microsoft Azure has come up with a collection of Speech Recognition AI Tools. Some of them are: Translator Speech API, Custom Speech Service, Speaker Recognition API and Bing Speech API. Allowing you to interact with your devices using voice commands, the above tools recognize your speech and convert it into text that the device can understand and process.

Let us now move on to the Language-Centric AI Tools offered by Microsoft Azure.

Text Analytics API, Linguistic Analysis API, Translator Text API, Bing Spell Check API, Web Language Model API are some of the cognitive tools that can automate a number of natural language instructions.

Knowledge-Centric AI Tools such as Custom Decision Service, Recommendations API, Knowledge Exploration Service, Academic Knowledge API and Entity Linking Intelligence Service API are cognitive tools of Microsoft Azure. They help developers to represent global and educative information that a computer can reason-out and come up with solutions to specific tasks.

Some of the Search-Based AI Tools of Microsoft Azure include: Bing Video Search API, Bing Image Search API, Bing Web Search API, Bing News Search API and Bing Autosuggest API. All these are intelligent tools that will simplify your life in more ways than one. If one can look up for a video of your choice, the other can intelligently reduce the number of words to key in by automatically suggesting the next word. As if all these are not enough, you can effortlessly search for news articles from across the globe and experience the luxury of reading segregated information in the form of topic-wise news or regional news.

Conclusion: –
Driven by an intent to explore the intersection of human behavior and high-end life-changing technology, all the above AI tools come up as new ideas that can simplify our lives. Now is the age of huge investments in sourcing AI-optimized hardware, Deep Learning Platforms, Speech Recognition and Virtual Agents (Chat Bots). These intelligent options are all set to make life more exciting and simple for end-users and companies as well.

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