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Zero trust data pipeline framework
We have all experienced the pain of data loss or data incorrectness in our batch data pipelines. To address this, I designed a framework for ensuring data correctness at every stage o...
In journal, Feb 06, 2026Model inference in seldon kubernetes cluster
In this blog post, I’m sharing my journey of installing Seldon Core from scratch on my Mac. I started by setting up a local Kubernetes cluster and installing all the necessary depende...
In journal, Mar 09, 2025Synthetic data generation
In my current organization, I am working on a model to sort post-consumer clothes to make them easier to recycle into products of different grades.
In journal, Dec 27, 2024Dockerize whisper model
IntroductionWhat is a whisper model?Whisper is an open source speech recognition model trained by OpenAI. It enables transcription in multiple languages, as well as translation from t...
In journal, Apr 13, 2024Tunable loss functions for binary classification problems
Paper: Xtreme Margin: A Tunable Loss Function for Binary Classification Problems
In journal, Jul 16, 2023Image augmentation with imgaug
This is a code snippet to generate image augmentation on your training data.
In journal, Jul 04, 2023Google pegasus summarization model installation
In this blog post, I explain the steps that I followed to install google pegasus summatization model from the officical github page. I failed to complete the installation, since the p...
In journal, Jun 25, 2023DiffusionDet Inference
[11/25 00:30:07 detectron2]: Arguments: Namespace(confidence_threshold=0.5, config_file=’configs/diffdet.coco.res50.yaml’, input=[‘image.jpg’], opts=[‘MODEL.WEIGHTS’, ‘.\diffdet_coco_...
In journal, Nov 25, 2022Machine Learning and Deep Learning comparison
A Comparison of Traditional Machine Learning and Deep Learning in Image Recognition
In journal, Jun 05, 2022Siamese Network for duplicate detection
In this post, I will list out the application of Siamese network from the paper Using Siamese CNNs for Removing Duplicate Entries From Real-Estate Listing Databases.
In journal, May 05, 2022Low dimension neural network training
Deep neural networks can be optimized in randomly-projected subspaces of much smaller dimensionality than their native parameter space. While such training is promising for more effic...
In journal, Mar 31, 2022Gradio Tutorial
I recently had a POC to present to my team. It was an image similarity project in the retail space. I was looking for a simple tool to demo the top N similar image for a given query i...
In journal, Feb 01, 2022Segmentation data annotation cvat
In this article, I will walk you through the process of annotating images for instance segmentation using the cvat.org website.
In journal, Dec 17, 2021Serving Tensorflow to 300 million predictions per second
This paper presents the process of transitioning machine learning models to the Tensorflow framework at a large scale in an online advertising ecosystem.
In journal, Sep 24, 2021Statistically stopping of neural network training
Paper: Statistically Significant Stopping of Neural Network Training
In journal, Jul 03, 2021Visualize feature maps
In this article, I will visualize the feature maps in a neural network. Since the focus of this article is to visualize the feature maps, I am using a tutorial neural network training...
In journal, May 09, 2021Complete IoU
The loss functions are the major driving force in training a good model. In Object detection and Instance segmentation tasks, the most widely used loss function is Intersection over U...
In journal, May 09, 2020Understanding CNN
This is a summarization of the Explanatory Graphs for CNNs paper.
In journal, Jan 15, 2019Multi Target Prediction
In this blog, lets talk about multi target variables. In a generic machine learning model prediction scenario, where we will have input features and single target variable.
In journal, Dec 26, 2018Summary - Gradient Descent Finds Global Minimum
Gradient Descent Finds Global Minima of Deep Neural Networks
In journal, Nov 14, 2018Summary - Mask RCNN
MASK R-CNNFacebook AI Research (FAIR) Kaiming He Georgia Gkioxari Piotr Dollar Ross Girshick
In journal, Nov 10, 2018Summary - Google BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova
In journal, Nov 06, 2018Deep Learning interview questions.
Difference between Deep Networks vs Shallow Networks ?
In journal, Oct 31, 2018Summary - Super Resolution
Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network
In journal, Oct 29, 2018Summary - A Dataset and Architecture for Visual Reasoning with a Working Memory
In journal, Oct 13, 2018
Feed Forward Propagation from Andrew Ng Machine Learning Lecture
Neural networks are a series of stacked layers. Deeper the network, higher the number of layers. Layer 1 is called the input layer and Layer 3 is called the Output layer. The intermed...
In journal, Sep 27, 2018sample
Zero trust data pipeline framework
We have all experienced the pain of data loss or data incorrectness in our batch data pipelines. To address this, I designed a framework for ensuring data correctness at every stage o...
In journal, Feb 06, 2026Model inference in seldon kubernetes cluster
In this blog post, I’m sharing my journey of installing Seldon Core from scratch on my Mac. I started by setting up a local Kubernetes cluster and installing all the necessary depende...
In journal, Mar 09, 2025Synthetic data generation
In my current organization, I am working on a model to sort post-consumer clothes to make them easier to recycle into products of different grades.
In journal, Dec 27, 2024Dockerize whisper model
IntroductionWhat is a whisper model?Whisper is an open source speech recognition model trained by OpenAI. It enables transcription in multiple languages, as well as translation from t...
In journal, Apr 13, 2024Tunable loss functions for binary classification problems
Paper: Xtreme Margin: A Tunable Loss Function for Binary Classification Problems
In journal, Jul 16, 2023Image augmentation with imgaug
This is a code snippet to generate image augmentation on your training data.
In journal, Jul 04, 2023Google pegasus summarization model installation
In this blog post, I explain the steps that I followed to install google pegasus summatization model from the officical github page. I failed to complete the installation, since the p...
In journal, Jun 25, 2023DiffusionDet Inference
[11/25 00:30:07 detectron2]: Arguments: Namespace(confidence_threshold=0.5, config_file=’configs/diffdet.coco.res50.yaml’, input=[‘image.jpg’], opts=[‘MODEL.WEIGHTS’, ‘.\diffdet_coco_...
In journal, Nov 25, 2022Machine Learning and Deep Learning comparison
A Comparison of Traditional Machine Learning and Deep Learning in Image Recognition
In journal, Jun 05, 2022Siamese Network for duplicate detection
In this post, I will list out the application of Siamese network from the paper Using Siamese CNNs for Removing Duplicate Entries From Real-Estate Listing Databases.
In journal, May 05, 2022Low dimension neural network training
Deep neural networks can be optimized in randomly-projected subspaces of much smaller dimensionality than their native parameter space. While such training is promising for more effic...
In journal, Mar 31, 2022Gradio Tutorial
I recently had a POC to present to my team. It was an image similarity project in the retail space. I was looking for a simple tool to demo the top N similar image for a given query i...
In journal, Feb 01, 2022Segmentation data annotation cvat
In this article, I will walk you through the process of annotating images for instance segmentation using the cvat.org website.
In journal, Dec 17, 2021Serving Tensorflow to 300 million predictions per second
This paper presents the process of transitioning machine learning models to the Tensorflow framework at a large scale in an online advertising ecosystem.
In journal, Sep 24, 2021Statistically stopping of neural network training
Paper: Statistically Significant Stopping of Neural Network Training
In journal, Jul 03, 2021Visualize feature maps
In this article, I will visualize the feature maps in a neural network. Since the focus of this article is to visualize the feature maps, I am using a tutorial neural network training...
In journal, May 09, 2021Complete IoU
The loss functions are the major driving force in training a good model. In Object detection and Instance segmentation tasks, the most widely used loss function is Intersection over U...
In journal, May 09, 2020Understanding CNN
This is a summarization of the Explanatory Graphs for CNNs paper.
In journal, Jan 15, 2019Multi Target Prediction
In this blog, lets talk about multi target variables. In a generic machine learning model prediction scenario, where we will have input features and single target variable.
In journal, Dec 26, 2018Summary - Gradient Descent Finds Global Minimum
Gradient Descent Finds Global Minima of Deep Neural Networks
In journal, Nov 14, 2018Summary - Mask RCNN
MASK R-CNNFacebook AI Research (FAIR) Kaiming He Georgia Gkioxari Piotr Dollar Ross Girshick
In journal, Nov 10, 2018Summary - Google BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova
In journal, Nov 06, 2018Deep Learning interview questions.
Difference between Deep Networks vs Shallow Networks ?
In journal, Oct 31, 2018Summary - Super Resolution
Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network
In journal, Oct 29, 2018Summary - A Dataset and Architecture for Visual Reasoning with a Working Memory
In journal, Oct 13, 2018
Feed Forward Propagation from Andrew Ng Machine Learning Lecture
Neural networks are a series of stacked layers. Deeper the network, higher the number of layers. Layer 1 is called the input layer and Layer 3 is called the Output layer. The intermed...
In journal, Sep 27, 2018