Monthly Archives: September 2020

1D-CNN based Fully Convolutional Model for Handwriting Recognition

Handwriting

Handwriting Recognition also termed as HTR(Handwritten Text Recognition) is a machine learning method that aims at giving the machines an ability to read human handwriting from real-world documents(images). The traditional Optical Character Recognition systems(OCR systems) are trained to understand the variations and font-styles in the machine-printed text(from documents/images) and they work really well in practice(example-Tesseract). Handwriting Recognition on… Read More »

Optimizing TensorFlow models with Quantization Techniques

https://www.codesofinterest.com/2019/10/tensorflow-20-released.html

Deep Learning models are great at solving extremely complex tasks efficiently but this superpower comes at a cost. Due to a large number of parameters, these models are typically big in size(memory footprint) and also slow in the inference (during predictions). Slow and heavy models are not much appreciated when it comes to the deployment part. As we… Read More »

Sampling Techniques in Statistics for Machine Learning

Sampling | dropsofai.com

Data is like a fuel to a Data Scientist. Any study or research work requires a good amount of quality data. The term ‘good amount of quality data’ changes with the kind of study one wants to do. Various sampling techniques are there to get you just that. As a researcher, you may want to study-different animals, changing… Read More »