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Hackernoon logoTell If Your SMS is Spam by@navneet-madhu-kumar

Tell If Your SMS is Spam

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@navneet-madhu-kumarNavneet Madhu Kumar

Data Scientist


Natural Language Processing. Machine Learning. Deep Learning. Transformers. LSTMs. All these seem jargon to you or never got around the thousands of lines of code and ‘tricks’ to use them? Then this post is for you.

The field of Machine Learning and Natural Language Understanding has seen rapid development in the past couple of years, thanks in no part to Deep Learning. Current AI has shown amazing leaps in performance on tasks with limited data with the help of Transfer Learning. For those who don’t know what that is… It is basically a magical tool that allows anyone to take existing AI models and train them for their own data, however, small the dataset maybe. Sounds good, right?

The harsh truth is that getting these models to work requires substantial knowledge of coding, machine learning, and deep learning. And even if you have the prerequisite knowledge, it can still be a very daunting task. Extremely daunting.

Introducing — A no-code platform that allows anyone, with no experience in machine learning and coding, to build, train and deploy data classifiers.

Based on the awesome Huggingface Transformers Library

So How does Aasaan work?.

We will be using the Spam Classification Dataset for this task.

First step: Go to

Upload your dataset to Aasaan.

The first step is, obviously, uploading the dataset to Aasaan. At the moment, the platform only supports CSV files but we plan to add many more formats in the future.

For this example, you can download SMS Spam Dataset.

Once you upload the CSV, Aasaan shows you an overview of the dataset.

Now, select the column with the text that you wish to classify.

At this point, you have the option to use the labels in your dataset (if you have those). We will be selecting Column 1 for the dataset and Column 0 for the labels.

Train the model.

Now relax. Wait for a few minutes while Aasaan trains for you.

Evaluate the model.

Add the text and just press predict. Or you can use the CSV tab to add your test CSV file.

For using the API or Marketplace tab, you need to join our waiting list. It is free and we would love to have your feedback.

Not too shabby for something made in a few minutes. Such is the power of deep learning and transfer learning now you can leverage it too. Without breaking a sweat.


We have successfully built, trained and deployed a data classifier without:

  • Writing a single line of code
  • Configuring any GPU
  • Looking at daunting documentations
  • Reading and understanding of machine learning papers.
  • Visit us at Aasaanai to try for yourself and be an early beta tester and join our waiting list!


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