What Is AWS SageMaker: Features, Pros, Cons + How To Use

Are you aware of the revolutionary data analytic & prediction service the whole world is talking about? If not, read this to know about What Is AWS SageMaker.

Artificial Intelligence has developed leaps and bounds in the 21st Century. From being a novel science fiction idea in the 1980s and 90s, it is now a living reality thanks to services like AWS SageMaker.

You can now train your machines to learn how to analyze the data generated by your business and make accurate predictions regarding how it is performing. It can tell everything, from if you are doing well to if you need help. It can even tell you what changes are needed.

A significant reason we can accomplish this is because of the efforts put forward by companies like Amazon Web Services, as they are one of the companies leading the charge for tech development. Today, we are talking about their machine learning service: Amazon SageMaker.

Explaining What Is AWS SageMaker?

Amazon SageMaker is a service offered by Amazon Web Services. This service helps you supervise, instruct, and release machine learning models for your business.

This service can help you expedite your business growth as SageMaker is considered an AI service that can analyze your business data. It notifies what you are doing well and what needs to change.

What Is A Machine Learning Model?

Before we discuss Amazon SageMaker in further detail, we would first like to highlight what a machine learning model is, what they are used for, and the benefits it can serve your business. So for those uninitiated regarding machine learning, keep reading ahead.

Machine learning models is a software that performs multiple jobs for you. Their jobs consist of analyzing data, learning from it, and analyzing competitors’ markets to make predictions.

Their predictions consist of how well or badly your business is performing, what your competitors are doing, where you are going wrong, and even what you need to do to attain or surpass your competitors’ success.

Why Are Machine Learning Models Used?

The primary reason machine learning models are used is to do the arduous yet important task of data extraction, analysis, processing, and result findings.

Machine learning models can detect your business’s problems and tell you how to fix them. They can even learn and adapt to newly established problems and help you deal with them. Utilizing their service, you are always one step ahead of the competition.

Benefits Machine Learning Models Can Serve You?

The following are the perks when you utilize machine learning models:

Functions Amazon SageMaker is Used For?

The following are the core functions AWS SageMaker is used for:

1. AWS SageMaker Provides Expert Business Analytics

The foremost function you can use Amazon SageMaker for is expert business analytics. SageMaker provides data comprehension, breakdown, and recommendations, unlike any other service.

2. Data Scientists Can Use Amazon SageMaker To Prepare & Analyze Any Data

The second function Amazon SageMaker is useful for is the versatility of data it can process. Regardless of the business, niche, or industry, SageMaker can handle all data with utter competence.

3. Machine Learning Engineers Use Amazon SageMaker To Develop & Deploy New Tech

The final function Amazon SageMaker provides is that machine learning engineers can use it to develop new technology. Its adaptability makes it the perfect service that can handle any workload.

Hence, they use it to feed their algorithm and deploy new research and development technology. Amazon SageMaker absorbs and interprets data competently, hence, ML engineers love working with it.

Benefits of Using Amazon SageMaker Over Other Machine Learning Services

You gain the following benefits when using Amazon SageMaker over other machine learning services:

1. Amazon SageMaker Offers Usability For People of Various Backgrounds

We believe the most significant benefit of using Amazon SageMaker is that it is user-friendly for people of all backgrounds. So, whether you are a business analyst or a software programmer, you can use it with complete ease.

Whether you want to check if the program machine learning coding is going according to plan or if you want data visualized in analytics form, Amazon SageMaker can do it all.

2. It Allows You To Analyze & Predict Data of Any Size

The second prominent benefit Amazon SageMaker serves is the capacity and capability to analyze data because regardless of the amount of data you are trying to process, it can handle it all without a hitch.

 Plus, in addition to analyzing, it also provides accurate predictions of how the data is performing and suggestions for how it can be improved.

3. AWS SageMaker Expedites The Machine Learning Progress In Your Organization

Machine learning is essentially empowering your software through customized codes and algorithms, no other service improves its performance as Amazon SageMaker does.

It can expedite the learning progress of machine learning in your organization because this service provides you with code customization ability that no other machine learning service does.

4. Amazon SageMaker Manages Machine Learning Operations Better Than Everyone

Connected to the third benefit, the fourth benefit of Amazon SageMaker is that it manages machine learning operations better than any other service.

It gives you the freedom to process data, make predictions, or choose the analysis you want. No other service can even come close to the competency they provide you.

5. SageMaker Provides Expert Integration With Other AWS Services

Another significant benefit of AWS SageMaker is that it can integrate with other AWS services. This effectively means you can use all the AWS services to support your application development while using SageMaker.

6. Amazon SageMaker Can Protect You From Fraud Detection

The machine learning aspect of Amazon SageMaker can be defined by this advantage alone. Once you feed it the custom code and algorithm you want, this service can learn to detect fraud.

So if a bot or a real-life scammer is trying to scam you, then this service will highlight it in an instance. It will even explain how it believes the transaction is fraudulent.

7. Receive Personalized Recommendation For Better Use

We believe the best advantage Amazon SageMaker serves is that, unlike other machine learning models, it doesn’t provide generic remarks.

It comprehends your data in-depth and provides personalized recommendations for whatever scenario you are running it for. It provides you with the best options available.

Limitations of Amazon SageMaker

Amazon SageMaker is a market-leading, completely managed machine learning model service. Yet it isn’t the perfect service; we believe this because it has the following limitations.

Users Have Complained there is a Lag when Handling Bulk Data

Even though Amazon SageMaker can process data in bulk quantity, some of its users have complained that it can cause a time lag.

So if you are a business that relies on rapid speed to make decisions regarding your business, this could be a potential problem for you.

Multiple UI Graphics Can Confuse Professionals

One benefit of Amazon SageMaker is also a limitation, as this service provides you with multiple graphics representing different data for different professionals.

For analysts, it can provide data analysis. For programmers, it can showcase program code, but for professionals who are not linked to these industries or are new hires, this could prove to be confusing.

Training Modules For Beginners Can Be Overwhelming

Many users have complained that the training module for beginners provided by Amazon SageMaker is complex and can overwhelm them. Other ML services have easier modules.

Companies That Employ AWS SageMaker For Their Business

The following are the major companies that employ Amazon SageMaker for the progression and success of their business:

Jobs Amazon SageMaker Can Accomplish?

The following are the jobs Amazon SageMaker is designed to accomplish

Sagemaker Pricing

Sagemaker is basically free for the first 2 months with some limitations to the type of machine you can use.

Along with the free tier we have on-demand pricing depending on the vCPU, and Memory and of course, on the type of machine, you are using.

For more details on the pricing, you can refer to the AWS documentation here.

How to create sagemaker with terraform?

The below code snippet creates a Sagemaker instance with a role assigned to it.

Amazon SageMaker FAQs

Final Word

21st-century technology is advancing at an incredible pace. So if you wish to keep up with it and make your business successful, then you need services like AWS SageMaker.

Hence, we have explained them in great detail. What do you think about them? Let us know in the comments section.

Steve

I am an Amazon Web Services Professional, having more than 11 years of experience in AWS and other technologies. Extensively working in various AWS tools like S3, Lambda, API, Kinesis, Load Balancers, EKS, ECS, and many more. Working as a Solution Architect and Technology Lead for Architecting and implementing the same for different clients. He provides expert solutions around the world and especially in countries like the United States, Canada, United Kingdom, Australia, New Zealand, etc. Check out the complete profile on About us.