Akshat Singhal (akshatsinghal92)

akshatsinghal92

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Akshat Singhal's repositories

AWS-Video-translation-and-subtitle-generation-

Used AWS services like Amazon Transcribe, Amazon Translate and Amazon Polly to generate multi language subtitles and multi language audio for a given input video and embed into a single output video.

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Product-recommendation-analysis

Predicting product recommendation score using the data available on the website of the client

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Battle-of-Neighbourhoods

Predicted the best neighbourhood in entire Toronto for the purpose of opening up a new restaurant.

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Credit-Risk-Estimation

Predicted whether a client should be approved for a loan based on their credentials, income, and previous credit history about them.

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Goal-Prediction

Predicted whether Cristiano Ronaldo will score a goal or not based on the data describing the shot he made.

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Virtual-Assistant

Implemented a simple Chat-bot using SEQ2SEQ Deep NLP model.

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dgl-ke

High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.

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Disaster-Tweets-Classification

Developed a framework to segregate fake disaster tweets by modelling LSTM networks and BERT

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NLP-Specialization

NLP Specialization (Natural Language Processing) made by deeplearning.ai

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PSI_AUG

PSI_AUG

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Publicis-Sapient-POD-2

A cancer tumor can have thousands of genetic mutations. Currently this interpretation of genetic mutations is being done manually. This is a very time-consuming task where a clinical pathologist has to manually review and classify every single genetic mutation based on evidence from text-based clinical literature.

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TensorFlowBasics

Code for the TensorFlow Tutorial | Deep Learning Using TensorFlow | TensorFlow Tutorial Python | Edureka (https://www.youtube.com/watch?v=yX8KuPZCAMo) with small corrections and additions of missing parts by Claude COULOMBE - PhD candidate TÉLUQ / UQAM - Montréal

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Text-processing-NLP

This notebook contains entire text preprocessing pipeline for NLP problems. The ready-to-use functions require NLTK and SKlearn package installations. It also contains some prominent text classification models.

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Titanic-Analysis

Predicted how many people survived in the Titanic incident.

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