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accadamic_programmes

this is a list programmes i did for practice for the accadamic session of 2017-21.

ai-dancer

angulartut

artificial-neural-networks

blue-cloud

cheater

chia-blockchain

Chia blockchain python implementation (full node, farmer, harvester, timelord, and wallet)

confluence-2019-auto

coursera_capstone

This repository is built as a part of certification course by IBM

covid-tracker

desktop-assistant

detectron2

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

facematch

Face match in python using Facenet and their pretrained model

facenet

Face recognition using Tensorflow

flask-test

testing

gpt-3

GPT-3: Language Models are Few-Shot Learners

hand-writen-number-classification

hydpy

HydPy - Hyderabad Python User Group Website

ibm-call-for-code

image-processing-between-cats-and-dogs

inpycon2018

PyCon India 2018 site

introduction-to-self-driving-cars

java-accadmic

academic java data

keras

Deep Learning for humans

keras-english-resume-parser-and-analyzer

keras project that parses and analyze english resumes

linkedin-skill-assessments-quizzes

Full reference of LinkedIn answers 2022 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers

magicprint-ecommerce-app-android

E-Commerce App Source Code for Android with Material Design Pattern Using Firebase and MySQL with Android Lottie Animations just like Flipkart, Myntra and Amazon :)

medical-expert-system-knowledge-base

Using expert system shells for the development of Expert systems. These shells are empty Expert System knowledge bases, which have the structure and interface already written for us; all we need to do is to add the knowledge into the KB. Instead of writing an Expert System from scratch, for this problem we will be using a small Expert System shell to design and implement an expert system. We used PyKnow Framework for building the concerned expert system.

models

Models and examples built with TensorFlow

mtcnn-head-detection

Head detection with modified cascaded CNN