Mir Nawaz Ahmad's repositories
Data_Extraction_and_Text_Analysis_for_Blackcoffer_company.
The objective of this assignment is to extract textual data articles from the given URL and perform text analysis to compute variables that are explained
Real-time-Human-Detection-and-Counting
In this python project, we are going to build the Human Detection and Counting System through Webcam or you can give your own video or images. This is a deep learning project on computer vision, which will help you to master the concepts and make you an expert in the field of Data Science. Let’s build an exciting project.
Emotion-detector-for-Twitter-messages
• Trained and deployed emotion detector with Word Embeddings, LSTM, BERT using TensorFlow and Transformers. • Fine tunned the Bert-base-cased Encoder Transformer with Tensorflow classification head, provides prediction out of 6 different emotions of the given input tweet with 95% accuracy.
Predicting_customer_churn
• Did in depth exploratory data analysis on the churn dataset and got valuable insight for the machine learning model. • Created a machine learning model using a bunch of algorithms (LR, KNN, SVC, Random Forest, Gradient Boosting) to predict customer churn based on historical data.GB classifier achieved 8% decrease in the overall churn rate
Retail-Prize-Optimization-based-on-Prize-Elasticity
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.
Airline-Travel-Information-System-ATIS-Text-Analysis
In this project, you will learn how to generate a complete semantic parse of utterances. First, you will make a discovery on your dataset to get insights about the dataset analytics. Then, you will learn, to extract entities with two different techniques – with spaCy Matcher and by walking on the dependency tree. Next, you will learn different ways of performing intent recognition by analyzing the sentence structure. Finally, you will put all the information together to generate a semantic parse.
Basket-Analysis-based-on-Customers-Behavior
Imagine if you are a retail business owner who owns a retail shop that sells hundreds of items. In a single month, there are more than a hundred transactions occurring in your shop, for instance. Each transaction is usually made with more than an item to be bought. It means there are usually more than an item in a single transaction.
End-to-End-Credit-Card-Fraud-Detection
This repository contains the procedure we followed to deploy our web app of Credit Card Fraud detection on Heroku. Since the data for credit card fraud is not available in real form(due to confidentiality), and is available only in dimensionality reduced form, we will be sharing some of the test cases here.
End-to-End-Movie-Recommendation-System
This is a Hollywood movie recommendation system built with Python. I have used IMDB 5000 Movie Dataset to built this. I have used Flask framework to built web app.
Image-Segmentation-using-PixelLib
PixelLib uses object segmentation to perform excellent foreground and background separation. It makes possible to alter the background of any image and video using just five lines of code.
INSAID_fruad_detection_model
This case requires trainees to develop a model for predicting fraudulent transactions for a financial company and use insights from the model to develop an actionable plan.
Real-Time-Covid-19-Face-Mask-Detection
Our face mask detector doesn't use any morphed masked images dataset and the model is accurate. Owing to the use of MobileNetV2 architecture, it is computationally efficient, thus making it easier to deploy the model to embedded systems (Raspberry Pi, Google Coral, etc.).
Supermarket-Sales-Analysis
Before venturing on to any data science project it is important to pre-process the data and also to explore the data. Today we will discuss a very basic topic of exploratory data analysis (EDA) using Python and also uncover how simple EDA can be extremely helpful in performing preliminary data analysis. The approach we will follow today is ask some questions and try to get those answers from the data. We will consider the supermarket sales data from the Kaggle dataset.
Time-Series-Analysis-
Time Series Analysis
Time_Series_EDA
Time_Series_EDA
udemy-downloader-gui
A desktop application for downloading Udemy Courses
Amazon-Food-Reviews-Sentiment-Analysis
• Conducting Sentiment Analysis of customer feedback on food items through the use of Machine Learning techniques. • Built a sentiment Classifier using LSTM along with various embedding techniques to classify given feedback/review of the food item as negative, neutral or positive.
academicstoday-django
A open-source platform for online course-based learning and education.
Awesome-CS-Books-Warehouse
:books: Awesome CS Books/Series(.pdf by git lfs) Warehouse, ProgrammingLanguage, SoftwareEngineering, Web, AI, ServerSideApplication, Infrastructure, FE etc. :dizzy: 优秀计算机科学与技术领域相关的书籍归档
awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
canvas-lms
The open LMS by Instructure, Inc.
django-LMS
A Leave Management System using Django.
flutter
Flutter makes it easy and fast to build beautiful mobile apps.
Kurteyki
LMS (Learning Management System) & Blog
LMS-1
LMS is a web based platfotm which is accessible, powerful, and provides tools required for large, robust learning platforms.
richie
:pencil: A CMS for Open Education to build learning portals
ulearn
ULEARN - Open Source(FREE) LMS script in Laravel 5.8 and ReactJS 16.9