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7 Advanced Platform as a Service Solutions Every Machine Learning Professional Should Use

Just like every other technology, machine learning has its advantages, disadvantages, and challenges.  According to statistics, businesses that adopt machine learning and artificial intelligence boosted their productivity by 40%, which also had a positive impact on their revenue. The ability to find patterns in large data sets and unearth useful insights is an invaluable asset in today’s data-driven world.

That is why most businesses have either adopted or planning to adopt machine learning. This will send the demand for machine learning professionals to surge as new jobs are created in the industry. We might see its new use cases and new applications being developed as machine learning continues to enhance the user experience.

If you are a fresh graduate who is thinking about pursuing a career in this lucrative field, you should also be aware of its fair share of challenges before dipping your toes in the industry.

Here are some of the machine learning challenge businesses face:

  • Scalability
  • Higher cost of deployment
  • Longer deployment cycle
  • Lack of machine learning experts

Thankfully, you can get over most of these challenges if not all them by using a machine learning platform. Which machine learning platform should I choose and why? That is the question we will try to answer in this article.

In this article, you will learn about seven platforms as a service solution every machine learning professional should be using right now.

IBM Watson Studio

If collaborative machine learning development is your priority, then look no further than IBM Watson Studio. Backed by IBM’s powerful cloud computing capabilities and top-of-the-line cloud infrastructure, users can perform advanced data analytics especially if they have a high-speed internet connection. You don’t need to buy VPS or dedicated servers for this purpose. Its intuitive user interface combined with easy-to-export architecture makes it an ideal choice for projects where you have to move the data architecture of a project and reuse it for another project.

The steep learning curve coupled with a lack of documentation, tutorials, and other supporting materials makes it difficult for new users to settle in. Since the platform as a service solution is tightly knit with IBM API, you might have to compromise on third-party data sources and API integration.

Azure Machine Learning Studio

Azure machine learning studio is one of the most popular machine learning platforms out there. With a large collection of ready-made examples and code snippets to choose from, machine learning developers can quickly get their machine learning projects off the ground.

What makes this machine learning tool stand out from the crowd is its backend which is dedicated to machine learning. This means that the backend comes pre-loaded with the machine learning libraries. It helps machine learning developers overcome scalability issues by enabling users to build, scale and deploy predictive models without any hassle. What’s more, users can also run, analyze and monitor experiments effectively and also take advantage of its huge library of readymade models.

Amazon SageMaker

If you are looking for a platform online store that is tailor-made for machine learning, then Amazon Sage Maker is an ideal choice. This platform as a service solution not only allows developers to create their own machine learning models but also lets developers choose machine learning models created by community members or add their own machine learning model to the platform.

By harnessing the power of cloud computing in Amazon Business Account , Amazon SageMaker offers a scalable cloud platform for machine learning where developers can create, train, test and deploy machine learning models rapidly. Thanks to the integration with Jupyter Notebook, users can perform all the tasks without having to switch platforms. This tool also gives you access to a huge repository of pre-trained data, which makes it easier for you to train your machine learning models quickly.

Deep Cognition

Ever wished there could be a way to automate your machine learning processes without having to write a single line of code? Deep cognition grants you your wish by delivering an intuitive graphical workflow. Users can input data, define its flow and train their model on a consistent basis to enhance its prediction capabilities. This platform lays a lot of emphasis on deep learning which is why you will find pre-configured models ready to perform specific tasks along with machine learning tools to train your machine learning models.

DataRobot

For those looking for an automated solution to fine-tune their machine learning models, there is no better option than DataRobot. With hundreds of open sources, pre-built and configured libraries to choose from, DataRobot’s powerful algorithm makes analyzing data a breeze. Users can ingest your data and make desired predictions and create a model which is ready to make predictions. To top it all off, it even lets you compare and visualize the outcome of different machine learning models. Deploying your machine learning model after comparison is just a matter of a few clicks.

Dataiku

If you want an all-in-one, enterprise-grade solution that can accommodate everyone from data scientists to AI developers, business analysts to data analysts and everyone in between, then Dataiku is for you. Since this platform supports most of the programming languages used in data science, you can use any programming language with this tool. Plotting data points is a breeze thanks to its visual data visualization tools. You do not even have to download popular machine learning libraries as they come built-in with Dataiku.

C3-AI Studio

For those who want more features than average, a C3-AI suite might win their fancy. With an exhaustive list of AI tools and features, you will find all the features you need and even more. Most of the algorithms are preloaded into the suite which allows machine learning developers to get a head start on their development journey.

It also gives you the freedom to choose data structure, storage, and computation resources according to your needs and can even connect with popular cloud storage services. C3-AI Studio can also handle batch processing and also give users a slew of visualization tools to visualize not only data but even workflows.

Which platform as a service machine learning solution does your business use? Let us know in the comments section below.