Blog

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AutoML with AutoKeras

Applications of deep learning in real world scenarios have increased, yet it requires an expert to build the model and tune it to improve the accuracy. Various stages in machine learning includes

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Visually Debug, Log and Test an Image Processing Code Using OpenCV and Python

As a Programmer, we are well familiar with logging, debugging and testing our regular program.

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Rails, Vue.js, GraphQL, and the bigger picture.

Nowadays I often come across this one buzz word ‘GraphQL’ and when I saw these lines

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Custom object training and detection with YOLOv3, Darknet and OpenCV

This paper gives more details about how YOLO achieves the performance improvement.

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Upload Multiple Files in Rails API using CarrierWave

A file can be uploaded to server in two ways, one we can send the image as base64 string as plain text and another one is using multipart/form-data .

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Using Multiple Elastic Search in Rails

For the Multi Database support i.e. managing model-specific database connection, we were waiting for Rails 6. It enhances our application to scale on the database level. You can check the below blog for some more details.

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Get Started with Machine Learning in Visual Studio Code and Jupyter

In General, we will be often switching to the browser for executing the Jupyter notebook file (.ipynb) while we spent the most time with our favorite Visual Studio Code Editor for editing .py file.

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Get Started with Machine Learning — Handy Python Tools

As part of the machine learning series, this article covers the necessary environmental setup to get hands dirty with machine learning in python.

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Using Machine Learning for Color Calibration with a color-checker

Computer Vision plays a vital role in Artificial Intelligence. In Francium Tech, we have delivered numerous solutions specifically in that field. Especially in Document segmentation, Noise document removal, Form Detection, Optical character recognition, Face Authentication and video Anti-spoofing, etc.,

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Configuring Horizontal Autoscaling in Kubernetes

With the advent of Kubernetes, simply a lot of hassles in managing the cluster of servers have gone away. One of the pain points in managing a cluster of servers in the aspect of scalability is autoscaling. When we need to scale up the servers to process thousands of jobs in the queue, we would need to launch multiple servers. This can be done manually either by issuing commands manually or an admin clicking a button on the UI of the application. We can avoid even that with Kubernetes.

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Deploying Machine Learning Model to AWS Lambda with Serverless

Deploying the machine learning model to AWS lambda is a well-known step. That is.,

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Reload your Vim Configs like a pro

Vim is a very powerful and addictive editor. If you want to know about vim check here.

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