Machine learning, the subset of Artificial Intelligence, allows systems to learn autonomously without explicitly programming them. They gradually improve their tasks by analyzing data and through their experiences.
However, there are different approaches to build an effective machine learning model. Most commonly, ML algorithms are trained on huge datasets where they learn to identify and make predictions. But for these, advanced machine learning tools are needed.
According to Statista, the machine learning market is expected to reach a whopping $298.70 billion. That indicates the demand for efficient machine learning tools, as well as skilled machine learning engineers will be on the rise. Mastering various machine learning tools with the best artificial intelligence and machine learning certifications is recommended.
Machine learning tools are broadly classified into two categories; open-source frameworks and cloud-based platforms. While open-source frameworks like TensorFLow and PyTorch are powerful libraries that form the building block for custom models, cloud-based platforms including Amazon SageMaker and Microsoft Azure Machine Learning have built-in algorithms and features to integrate with other cloud services.
In the following infographic we explore the top machine learning tools that you must know about to advance in your artificial intelligence career. It mentions the tools and their unique features. Check it out now and also learn how to choose the right machine learning tool for your project.
