5 Best AI tools and ML frameworks

Artificial Intelligence (AI) adoption is growing rapidly across the globe. Industries like, manufacturing, healthcare, education, etc. are utilizing modern technology to enhance their efficiency. It is becoming more important than ever to process a large amount of data. But to do so, you need different AI tools and frameworks.

In this article, we are trying to share some details about the most popular Artificial Intelligence tools.

Scikit learn

Scikit-learn is a free open source ML framework for Python. It is one of the most popular ML libraries with features including vector machine, random forests, and k-neighbors, plus Python numerical and scientific libraries like NumPy and SciPy.

The platform is perfect for data mining, data analysis, and data visualization. This tool can be used for classification, regression, clustering, dimensionality reduction, model selection, and preprocessing, to name a few.

Tensorflow

This AI tool is developed to conduct deep learning neural networks and machine learning research. It is a semi-open-source library that allows developers to perform numerical computations. This library tool can be used to build and train neural networks in pattern recognition. The best part of Tensorflow is that when you can compose a program in Python while running on either your CPU or GPU.

Tensorflow is written in Python and C++ that enables distributed training.

Theano

This tool can be utilized for defining, optimizing, manipulating, and evaluating mathematical expressions using a computer algebra system. Theano is well adapted to deep learnings where you deal with lots of numerical tasks.

Theano is one of the oldest deep learning libraries created to make actualizing profound learning models.

Azure Machine Learning

Microsoft created Azure Machine Learning cloud-platform for deploying predictive models as analytics solutions. Even if you don’t have advanced programming skills, using this you can deploy predictive models. Also, it can be used to machine learning models, run algorithms, and create recommender systems, to name a few.

Azure Machine Learning is designed with a simple drag-and-drop interface. It also includes hundreds of built-in packages and support for custom code.

IBM Watson

IBM Watson is an open, multi-cloud platform that automates the AI lifecycle. This helps to create models from scratch faster as it comes with pre-built enterprise apps. It helps data scientists and developers work together to accelerate the process of moving to deployment and integrate AI into their applications.

It empowers organizations to tap into data assets and inject predictions into business processes and modern applications and then optimize business value with visual data science and decision optimization.