Machine learning is the study of computer algorithms that automatically improves with time with an increased number of data. It is no secret that Machine Learning and AI are the latest technological trends and talent in these fields is in high demand. According to Forbes, Machine Learning and AI's hiring growth for this role has grown 74% annually in the past 4 years and is expected to grow consistently in the next decade.

Knowing which skills are sought after helps professionals stay abreast of the latest trends and tools to work on and break into the field. With the competitive edge globally and its relevance in today's world, there is no dearth of Machine Learning tools in the market. Making the right choice is important and tricky but essential to make processes more efficient and faster. Here are a few popular Machine Learning tools to get you a kick start.

1. Google TensorFlow

   TensorFlow is an end-to-end open-source platform for machine learning for numerical computation using data flow graphs. TensorFlow is a rich system, consisting of a comprehensive, flexible ecosystem of tools and libraries for managing all aspects of a machine learning system. The flexibility of this tool to provide multiple models or multiple versions of the same model simultaneously is one of the key highlights of this tool.

2. Microsoft Azure Machine Learning

   Azure is a cloud computing platform that allows and empowers developers to build, train, and deploy machine learning models. Through ML Studio, people without a data science background or experience can also build data models through drag and drop gestures and simple data flow diagrams. Its powerful cloud-based predictive analytics is worth checking out.

3. Amazon SageMaker

   Similar to Azure, Amazon is a cloud computing platform that provides data scientists and developers with the ability to build, train, and deploy ML models effectively and quickly. Traditional ML development models are cumbersome and error-prone involving stitching together tools and workflows. SageMaker provides all the components in a single toolset, so models get to production faster and with precision.

4. IBM Watson

   Watson promises to build powerful ML models from scratch, in precision with an edge to let you automate the AI life cycle trained with your data. IBM Watson is pushing all the boundaries and is at the forefront of the new era of cognitive computing.

5. KNIME

   KNIME is a software-building tool used to create and production data science using an intuitive environment enabling productivity and efficiency. KNIME can integrate the code of programming languages like C, C++, R, Python, JavaScript, etc. With an easy to deploy and install model, it is one of the sought-after Machine Learning tools today.

The selection of a tool depends on one's requirement for the algorithm, level of expertise, and the price models of the tools. Our training provides you with knowledge and hands-on experience on projects which help you make intelligent decisions on which tool works best in a given situation.

Skill Sigma's Machine Learning course focuses on making you an industry expert with real-time projects and internships after the completion of the course.