Machine learning (ML) projects are one of the best ways to gain hands-on experience and improve applied machine learning skills. Machine Learning beginners and enthusiasts can take advantage of machine learning datasets available and get started on their learning journey. In this cheat sheet, we will look at the top 10 machine learning (ML) projects for beginners in 2020, along with the machine learning datasets required to gain experience of working on real-world problems. We have divided the projects based on tasks like classification, forecasting, prediction and mining. Here are the top machine learning projects you can explore in 2020.
For any large-scale computer vision application, one of the critical criteria to success is the quality and quantity of the training dataset required to train the relevant machine learning model. Open-source datasets such as ImageNet are sufficient to train machine learning models for computer vision applications that do not require high accuracy or are not too complicated, But for more complex use cases, obtaining a large amount of high-quality training data can be quite challenging, such as autonomous driving, safety monitoring systems, medical image diagnosis and more. In this article, we take a look at how to quickly create (including collection, labelling, and quality inspection) high-quality training data sets for various computer vision scenarios. Different types of machine learning modelling methods may use different types of training data. The main difference in data type is the degree to which it is marked.
And for in-house teams, labeling data can be the proverbial bottleneck, limiting a company's ability to quickly train and validate machine learning models. By its very definition, artificial intelligence refers to computer systems that can learn, reason, and act for themselves, but where does this intelligence come from? For decades, the collaborative intelligence of humans and machines has produced some of the world's leading technologies. And while there's nothing glamorous about the data being used to train today's AI applications, the role of data annotation in AI is nonetheless fascinating. Imagine reviewing hours of video footage – sorting through thousands of driving scenes, to label all of the vehicles that come into frame, and you've got data annotation.
There is no doubt that Google is an absolute giant in the IT world. It creates various software tools for almost any imaginable area of activity existing today. Whatever you could want, Google, probably, has a solution. Either it is a smart voice helper or an intelligent shopping list, it doesn't matter. Seriously, even special streaming platforms, music tools, and advanced culture applications - Google reinvented the internet and proposed an absolutely new ecosystem for users. Most likely, it is useful to have your thoughts in the Keep, or remember about appointment via Calendar, but does Google have any software for programmers?