nagapoornima22's starred repositories
FaceRecognition
Face Recognition using OpenCV in Python
facial-login-web
Web based facial Authentication system with flask server
facenet-realtime-face-recognition
A small-scale flask server facial recognition system, using a pre-trained facenet model with real-time web camera face recognition functionality, and a pre-trained Multi-Task Cascading Convolutional Neural Network (MTCNN) for face detection and cropping.
GMM_Digital_Voice_Recognition
基于GMM与MFCC特征进行数字0-9的语音识别，GMM，MFCC，语音识别，中文数据，sklearn，Digital Voice Recognition。
ai-ganpati
A face and speech recognition application used by new generation Indian Gods!
Voice-Authentication-and-Face-Recognition
Voice Biometrics Authentication using GMM and Face Recognition Using Facenet and Tensorflow
FAQChatbot
Set of scripts to build a chatbot which will answer based on the FAQs supplied.
Flask-ChatBot
A chat bot microservice that can be trained for different datasets.
flask-chatbot
ChatBot recreated on Flask, using jQuery and AJAX
Flask-API-Token
This project shows how api developers can add tokens to secure web service/api from extreme abuse by users.
ChatBot-Using-NLTK
The name of the ChatBot is PyBot because I love to do anything with python and made the whole project with it.This PyBot can learn reply from you intially and can reply to you on the next ocuurence .The main feature is it is a BlogBot where it contains a blogpage Database and it can reply to user query regarding to their blog.
BotValue-public
BotValue is a Python chatbot to translate Natural Language Requests into DB query. This version has an anonymized database of Partners.
Tensorflow-Chatbot
Tensorflow chatbot which is capable of interacting with user through Rest Api, Web interface, GUI and CLI.
Chatbot-with-Python-by-ganesh-kavhar
ganesh kavhar chatbot
FaceRecognitionPi
Face Recognition Based Attendance System
raspberry-pi-face-recognition
Face recognition with Raspberry Pi for IoT Environments
Raspberry-py-Facial-Recognition
Open CV based Raspberry py - Facial Recognition
PyBot-A-ChatBot-For-Answering-Python-Queries-Using-NLP
Pybot can change the way learners try to learn python programming language in a more interactive way. This chatbot will try to solve or provide answer to almost every python related issues or queries that the user is asking for. We are implementing NLP for improving the efficiency of the chatbot. We will include voice feature for more interactivity to the user. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation. NLTK has been called “a wonderful tool for teaching and working in, computational linguistics using Python,” and “an amazing library to play with natural language.The main issue with text data is that it is all in text format (strings). However, the Machine learning algorithms need some sort of numerical feature vector in order to perform the task. So before we start with any NLP project we need to pre-process it to make it ideal for working. Converting the entire text into uppercase or lowercase, so that the algorithm does not treat the same words in different cases as different Tokenization is just the term used to describe the process of converting the normal text strings into a list of tokens i.e words that we actually want. Sentence tokenizer can be used to find the list of sentences and Word tokenizer can be used to find the list of words in strings.Removing Noise i.e everything that isn’t in a standard number or letter.Removing Stop words. Sometimes, some extremely common words which would appear to be of little value in helping select documents matching a user need are excluded from the vocabulary entirely. These words are called stop words.Stemming is the process of reducing inflected (or sometimes derived) words to their stem, base or root form — generally a written word form. Example if we were to stem the following words: “Stems”, “Stemming”, “Stemmed”, “and Stemtization”, the result would be a single word “stem”. A slight variant of stemming is lemmatization. The major difference between these is, that, stemming can often create non-existent words, whereas lemmas are actual words. So, your root stem, meaning the word you end up with, is not something you can just look up in a dictionary, but you can look up a lemma. Examples of Lemmatization are that “run” is a base form for words like “running” or “ran” or that the word “better” and “good” are in the same lemma so they are considered the same.
Flask-Requests-for-rendering-a-page
This is a simple demonstration how we can use flask and requests module to initiate a get request a render a page providing some user information based on the json data.
katana-assistant
Text based assistant powered by Machine Learning and NLP
chatterbot-corpus
A multilingual dialog corpus
flask-chatterbot
Simple boilerplate for ChatterBot using Flask
Building-a-Simple-Chatbot-in-Python-using-NLTK
Building a Simple Chatbot from Scratch in Python (using NLTK)
ChatterBot
ChatterBot is a machine learning, conversational dialog engine for creating chat bots