Amazon Sagemaker: making machine learning more accessible to everyone

1. AMAZON SAGEMAKER: MAKING MACHINE LEARNING MORE ACCESSIBLE TO EVERYONE Machine Learning is the intelligence behind some of the world’s most powerful technologies. Amazon Sagemaker is an AWS service that enables enterprises to use Machine Learning at scale, bypassing the steep and costly learning curve to get started. www.urolime.com

2. Machine learning's popularity and demand have increased over the past few years. Most companies are opting for ML for their businesses to improve business operations, customer success, and connectivity, which helps in their business expansion. ML is a subset of artificial intelligence that helps businesses use data effectively. It helps in extracting important insights from the raw data, which can be used to resolve major business issues through various algorithms. In the digital era, most businesses are migrating towards cloud-native platforms like AWS. Many organisations are working on how to democratise ML so that every business can avail of its benefits. AWS, being a top player in the cloud industry, has figured out a way to democratise so that everyone (developers and organizations) can access ML effectively and smartly. Machine learning has a huge impact on businesses as it helps to create various revenue opportunities with the right data usage. But one has to understand the ML end-to-end process better as it is a bit difficult. Attending courses and understanding the process in detail is especially important for businesses that come from non-technical backgrounds and have financial constraints. The one- stop solution for such businesses is AWS cloud consulting as they conduct training sessions and guide you to implement ML at affordable prices depending on your business needs. Amazon Sagemaker: AWS launched Amazon Sagemaker in 2017, which is a cloud-machine learning platform and a fully managed service that helps developers and data scientists to build, train, and deploy machine-learning models quickly. It simplifies deploying ML top-quality models by eliminating the heavy lifting involved in each step of the process. It also enables the developers to deploy these ML models on embedded systems, which is a bit difficult in traditional methodology. Another advantage of using Amazon Sagemaker is that it resolves the challenge of creating a single toolset with all the components used for developing ML models, which are missing in the traditional ML development process. This increases the production rate of ML models with low cost and less work. Sagemaker has different tools that help in democratising machine learning. Sagemaker tools and their advantages: 1.Sagemaker Studio is a fully integrated development environment where developers can create ML modes quickly with minimum coding and reduce the cost of running ML overloads. It has inbuilt plugins which complete the majority of the work involved in creating ML models. 2.Sagemaker books help in easy collaboration with others as they help in the easy sharing of notebooks. This is possible with one-click Jupiter notebooks, which makes your work run smoothly without any interruption as all changes made will run in the background and are saved in the same place. www.urolime.com

3. 3.Sagemaker Autopilot can give full control and visibility to the ML models. This helps organisations use the data insights effectively and can be used to improve their business growth. This feature is only present in Amazon Sagemaker, which can make a difference. 4.Sagemaker ground truth helps you to manage and create accurate datasets quickly. Datasets are key in ML and for any business too. Businesses spend huge amounts on data labelling, but this reduces the cost by 60%, which can be spent on other key areas. 5.Sagemaker Canvas is a visual and point-click interface that helps business analysts make accurate predictions without writing a single line of code. To use this tool does not require any experience in ML. This tool helps businesses to build models very easily just by importing the data from other resources and selecting those values you want to predict. If you use the tool wisely, it helps the business stay one step ahead of the competition. Apart from the tools, it has unique features that help in simplifying the ML end-to-end process. Key features of Amazon Sagemaker: 1.It is compatible with popular ML and DL frameworks like TensorFlow, PyTorch, Chainer, Keras, etc. 2.Its distributed training library feature enables the quickest and easiest method to train ML datasets. 3.The Sagemaker debugger helps in optimising the ML models, which saves time and data loss. 4.The best part about Amazon Sagemaker is its pricing, as you pay only for what you use. This means every business can implement ML successfully. AWS DeepRacer Student League: To democratise ML, especially for students, AWS created this competition. This is a wonderful opportunity to test your ML and reinforcement learning (RL). RL is an advanced version of ML. Developers with any skill can get a chance to work with machine learning with the aid of cloud- based 3D racing simulators. They teach the foundations of machine learning concepts in detail. This competition is conducted every year to give opportunities for students to build ML models and understand the scope and value of machine learning in today’s world. There will be cash prizes as well, which makes this competition serious and exciting. To Sum Up: Machine learning is a powerful tool which can change the course of a business as it can make or fail a company. It heavily relies on usage. One has to be very responsible while creating and using ML models as data is at stake. To reap the benefits of Amazon Sagemaker, any company www.urolime.com

4. should hire AWS Consulting Services from a reputable, professional, and experienced AWS consulting firm. This is going to help your business grow in the coming years and earn more revenue. www.urolime.com