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Machine Learning is an element of the Artificial Intelligence universe. Machine Learning has opened up windows to the transformative future that lies ahead of us. Naturally, there is a surge in people taking up machine learning courses and machine learning certifications all over the world due to its immense popularity and usefulness.

As a subset, Machine Learning focuses on growing from observations and experiences. The popularity of machine learning certification courses on online training platforms indicates that this is the thing of the future. Coming to R, it is one of the major languages for data science because of its excellent visualization features, a growing ecosystem of third-party packages, and tools for machine learning interpretability. R has emerged as a fantastic tool for scientific computing and has powerful statistical libraries. Beginners commonly use R for exploring the data before applying any automated learning.

There was a time when machine learning datasets were scarce. Now, with the advancement in this field, datasets are readily available across the internet, but still, machine learning experts find it difficult to get relevant datasets for project ideas. By this post, we wish to change that.

"Train Custom Machine Learning Models Cloud AutoML is a suite of Machine Learning products that enables developers with limited machine learning expertise to train high quality models by leveraging Google's state of the art transfer learning, and Neural Architecture Search technology."

"Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models."

"automatic exploratory data analysis Making sense of data is one of the great challenges of the information age we live in. While it is becoming easier to collect and store all kinds of data, from personal medical data, to scientific data, to public data, and commercial data, there are relatively few people trained in the statistical and machine learning methods required to test hypotheses, make predictions, and otherwise create interpretable knowledge from this data. The Automatic Statistician project aims to build an artificial intelligence for data science, helping people make sense of their data."