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#!/usr/bin/python
# -*- coding: utf-8 -*-


class MLEngineer:

    def __init__(self):
        self.name = "Naim Shant"
        self.role = "Machine Learning Practioner, Python Deveoloper"
        self.language_spoken = ["Bangla", "en_US"]

    def say_hi(self):
        print("Thanks for dropping by, hope you find some of my work interesting.")


me = MLEngineer()
me.say_hi()

HeyπŸ‘‹, I'm Naim Shant !:computer:

I am a deep learning and machine learning practitioner and learner. I am here to solve things, Learning a lot in the process.

Updates:

  • πŸ‘― I’m looking to collaborate on Data Science, Machine Learning and Deep Learning
  • I’m also working on a Research paper related to Deep Learning and Power.

Find me around:

Language and Tools

Top Languages Naim's GitHub Stats

Quick Access:

- Fast.ai : 

​```python
!pip install -Uqq fastbook
import fastbook
fastbook.setup_book()

Naim Shant's Projects

awesome-pytorch-list icon awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

banglanmt icon banglanmt

This repository contains the code and data of the paper titled "Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, and New Datasets for Bengali-English Machine Translation" published in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), November 16 - November 20, 2020.

catr icon catr

Image Captioning Using Transformer

cbir icon cbir

🏞 A content-based image retrieval (CBIR) system

cs-4800-graphics-project icon cs-4800-graphics-project

Graphically Visualizing a Complex System with the Integration of Deep Learning Object Detection and Tracking

deep-makeover icon deep-makeover

Deep learning project to transform male portraits into female and vice versa

human-activity-recognition-using-recurrent-neural-nets-rnn-lstm-and-tensorflow-on-smartphones icon human-activity-recognition-using-recurrent-neural-nets-rnn-lstm-and-tensorflow-on-smartphones

This was my Master's project where i was involved using a dataset from Wireless Sensor Data Mining Lab (WISDM) to build a machine learning model to predict basic human activities using a smartphone accelerometer, Using Tensorflow framework, recurrent neural nets and multiple stacks of Long-short-term memory units(LSTM) for building a deep network. After the model was trained, it was saved and exported to an android application and the predictions were made using the model and the interface to speak out the results using text-to-speech API.

mmt icon mmt

Multi-Modal Transformer for Video Retrieval

modelcompare icon modelcompare

Practical Deep Learning System Performance-- Final Project

nlp-tutorial icon nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

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