🎉 Introduction 🎉

Today’s technological advancements are heavily dependent on the availability of structured data. Though data is available in huge quantities all over the internet, data collection and cleaning are major tasks for any kind of analysis or model development. This is where Scrapera comes in to save the day!

🙋‍♂️ About Scrapera 🙋‍♂️

Scrapera is an all-in-one tool for common scraping domains like image, text, audio, video, etc. Scrapera aims at clustering common scraping tasks under a single library which makes it convenient for users. With Scrapera, Data scientists and ML researchers can focus their time and energy towards creating better preprocessing pipelines and training…

Credits: Google

What is Active Learning?

Active Learning is a sub-field of Machine Learning wherein the model can query the user for desired information as the training process progresses. The user (or the Oracle) then labels the required data and adds it to the training samples. This way, the model can learn by active interaction with a human and unnecessary data structuring and annotations can be avoided.

This article aims at explaining the logic of active learning along with an example with the IMDB Sentiment Analysis dataset and Tensorflow 2.x

How does Active Learning work?

Credits: Zoom

At the time of boom of online video conferencing and virtual communication, the ability of a platform to suppress background noise plays a crucial roll to give it a leading edge. Platforms like Google Meet constantly use Machine Learning to perform noise suppression to provide the best audio quality possible. Today I will show you how you could make your own Deep Learning model to perform Noise Suppression

What’s the Big Deal with Noise Suppression?

The task of Noise Suppression can be approached in a few different ways. These might include Generative Adversarial Networks (GAN’s), Embedding Based Models, Residual Networks, etc. …

Darshan Deshpande

Machine Learning Engineer and a Mentor at Tensorflow UserGroup Mumbai

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