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ai201-project

SMART ATTENDENCE RECORD SYSTEM Project

ai351_lab

analyze-datasets-and-train-ml-models-using-automl

The Practical Data Science Specialization teaches you how to build and deploy machine learning projects using Amazon SageMaker. It's for developers, scientists, and analysts who already know Python and SQL and want to learn how to create scalable ML pipelines in the AWS cloud.

aws-texract-form1040

The following is the git repository for the Demo-Texract Project

build-train-and-deploy-ml-pipelines-using-bert

In the second course of the Practical Data Science Specialization, I learned how to automate a natural language processing task by building an end-to-end machine learning pipeline using Hugging Face’s highly-optimized implementation of the state-of-the-art BERT algorithm with Amazon SageMaker Pipelines.

chat-assitant-for-university-selection-using-openai-api

In our project what we propose to do is to train the gpt3 fined tuned model with the factual data according to the enrollment requirements so that the chat assistant can give more accurate and precise responses.

chatpdf-serverless

chordcraft

computer-vision

This repository contains all the codes I practiced for the understanding of computer vision.

cs232-project

cs423-assignment-2

This is repository of for hands-on on github Actions

cs423-assignment-4

This is the repository for Terraform hands-on

data-structure-project-spotify-

C++ based Spotify Project using Data Structures

deep-learning

demo-githubactions

this is a demo repository for github action

devops-assignment2

lab201

Lab tasks

nlp

This Repository contains all the codes related to Natural Language Processing

nlp_course

This repositry will contin the code done during the lectuers and class sessions at GIK Institute

nlp_lab_final

os_fall22

Resources for OS course

os_project

Operation System end of the semester project repository.

practical-data-science-on-the-aws-cloud-specialization

@DeepLearning.AI Practical Data Science Specialization brings together these disciplines using purpose-built ML tools in the AWS cloud. It has helped me to develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker.

rfq-pipeline

text-classification-of-movie-plots-to-predict-movie-genre

Movies are a popular means of entertainment all around the world. With a lot of streaming services and websites available and with more on the horizon, building a predictive model that automatically generates the genre of a movie based on the its plot summary is definitely beneficial as it may reduce the expense of manually tagging the movies.

textract-a21-form1040

texttoimg