Rishit Dagli's Blog

Rishit Dagli's Blog

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How to Start an Open Source Project on GitHub – Tips from Building My Trending Repo

Oct 15, 202114 min read

Originally published at https://www.freecodecamp.org on October 14, 2021. Developers around the world use GitHub to share their projects with the global developer community. In this article, I’ll give you some opinionated tips to help you build a ...

How to Start an Open Source Project on GitHub – Tips from Building My Trending Repo

How to Monitor Machine Learning Projects on Your Mobile Device📱

Aug 26, 20217 min read

Originally published on freecodecamp.org What if you could monitor your Colab, Kaggle, or AzureML Machine Learning projects on your mobile phone? You'd be able to check in on your models on the fly – even while taking a walk🚶. If you are an ML devel...

How to Monitor Machine Learning Projects on Your Mobile Device📱

How to Build Better Machine Learning Models

Apr 27, 202112 min read

Hello developers 👋. If you have built Deep Neural Networks before, you might know that it can involve a lot of experimentation. In this article, I will share with you some useful tips and guidelines that you can use to better build better deep learn...

How to Build Better Machine Learning Models

The Art of Hyperparameter Tuning in Deep Neural Nets by Example🎨

Jan 22, 202121 min read

Hello developers 👋, If you have worked on building Deep Neural Networks earlier you might know that building neural nets can involve setting a lot of different hyperparameters. In this article, I will share with you some tips and guidelines you can ...

💡TensorFlow Tip, use .cache

Jan 1, 20211 min read

Originally posted on twitter.com 💡#TensorFlowTip Use .cache to save on some ops like opening file and reading data during each epoch transformations before cache are only run for 1st epoch can cache in-memory or on-disk not repeatedly perform expe...

💡TensorFlow Tip, use .cache

💡TensorFlow Tip, use prefetch

Dec 13, 20201 min read

Originally posted on twitter.com 💡 #TensorFlowTip Use .prefetch to reduce your step time of training and extracting data overlap the preprocessing and model execution while the model executes training step n the input pipeline is reading the data ...

💡TensorFlow Tip, use prefetch