Understanding the importance of NoCode Machine learning tools and what the best ones in market?

Businesses today run on information and insights, which in turn, run on data. And to study this data that generally exists in an unstructured format, we need machine learning. Next, we also need AI to provide personalized services on a massive scale. However, the problem is that mastering machine learning is super hard and requires a time investment. Meanwhile, though businesses need decision-making insights about their customers, products, and usage to stay relevant in market flux, more than ever, for employees, it is frustrating to write SQL queries. Along with that, waiting on web engineers who would try to figure out algorithms proved quite arduous. Therefore, in a bid to ease such woes, companies are using NoCode platforms to deploy AI and machine learning models, giving them the ability to classify, extract, and analyze organizational data quickly. The NoCode tools are extremely easy to use with results on any query returned in under a minute. Users simply need to upload their dataset from CSV, databases, or CRMs and then get a Google-like search bar to ask a question in natural language. This enables them to create web and mobile apps by dragging and dropping elements, without getting bogged down in code.

While this sounds like a new concept, No- and low-code software development is just an extension of how programming has always evolved toward a more intuitive form. For instance, a spreadsheet is a kind of no- or low-code platform, enabling a user to analyze and manipulate data without writing hardly any code. These development platforms can help users unlock new opportunities worldwide to accelerate the promise of software sustaining the digital world by helping experts work more effectively and giving more people the ability to write software. Drivers of this trend arise from companies' intention to shift from traditional IT ecosystem and engineering teams into the line of business teams, increase productivity, and reduce costs due to more cloud-based applications. It is important to note that NoCode platforms can never completely replace hand-coded systems. Instead, they can help boost smaller, less experienced data science teams and prototyping for professional data scientists.

The NoCode platforms are proving to be the next battle frontier of the tech giants. Also, they are easily customizable. Analytics Insight brings this month's top No-Code Machine Learning platforms.

Create ML: Apple's no-code drag and drop tool, CreateML is the best platform for iOS developers. While initially launched with Xcode, today, CreateML is an independent macOS application that comes with a bunch of pre-trained model templates. In this, one can fine-tune the metrics and set customized iteration count before starting the training. It provides realtime results on the validation data for models such as style transfer. In the end, it'll generate a CoreML model that can be tested and deployed in iOS applications. It also permits to build models for object detection, activity, and sound classification. It also allows users to train their models from Apple with custom data and enhance performance using an external graphics processing unit.

Teachable Machine: Developed by Google, Teachable Machine is a browser-based system that records using the user's computer's webcam and microphone. This platform enables users to train models to recognize images, sounds quickly, and poses right from the browser. In this manner, one can teach the models to classify images, sound recordings, and body postures. The app provides the liberty of using files as well as capturing live examples from the spot. It runs on the Tensorflow.js library in the browser and ensures that the training data stays on the device.

Google AutoML:  This NoCode platform from Google Cloud is a suite of machine learning products that enables developers with limited machine learning expertise to train high-quality models specific to their business needs. It encompasses vision, natural language, AutoML translation, video intelligence, and tables. It removes the need to know transfer learning or how to create a neural network by providing out of the box support for thoroughly tested deep learning models.

Accelerite ShareInsights by Amazon Web Services (AWS): This NoCode tool allows users to design ETL pipelines without programming. A user can design ETL pipelines without programming, use cloud-native technologies, and create interactive dashboards in a matter of minutes. With the help of AWS services, the tool features a drag and drop console to create the pipeline. Accelrite Shareinsights is a complete data analytics platform for data on S3 or Redshift and also can optimize across Glue, EMR, Sagemaker, and Redshift Spectrum and enables anyone to use cloud-native technologies for creating interactive dashboards. Further, it provides end-to-end data preparation, OLAP, Data lake visual explorer, and machine learning as a single integrated process.

Obviously AI: This no-code tool allows users to upload their datasets from CSV, databases, or CRMs to summon a Google-like search bar to ask a question in natural language. The platform trains the machine learning model by choosing the right algorithm as per the user. It lets companies integrate data from other sources as well, such as MySQL, Salesforce, RedShift, and practice predictive analysis on business data. This tool was founded on the belief that business users should be able to get insights from their data, without waiting on an engineer. Currently, it supports CSV, MySQL, PostgreSQL, BigQuery, Redshift, Salesforce, and Hubspot.