Realtime Sign Language Detection: Deep learning model for accurate, real-time recognition of sign language gestures using Python and TensorFlow.

Model Evaluation is the process through which we quantify the quality of a system’s predictions. To do this, we measure the newly trained model performance on a new and independent dataset. This model will compare labeled data with it’s own predictions.

To import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. I will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them.

Data Preprocessing, Data Cleaning, Fine-tuning the Hyperparameters,

BC4AI：Blockchain Used to Guarantee Credibility of AI Model Evaluations;利用区块链来保证算法模型的真实性

A bike-sharing system is a service in which bikes are made available for shared use to individuals on a short term basis for a price or free. Many bike share systems allow people to borrow a bike from a "dock" which is usually computer-controlled wherein the user enters the payment information, and the system unlocks it.

The process of computationally identifying and categorizing opinions expressed in a piece of text, especially to determine whether the writer's attitude towards a particular topic, product, etc. is positive, negative, or neutral. Understanding people’s emotions is essential for businesses since customers are able to express their thoughts and fe…

Label-Free Model Evaluation and Weighted Uncertainty Sample Selection for Domain Adaptive Instance Segmentation

The objective of this project is to recognize hand gestures using state-of-the-art neural networks.

This repository contains code for evaluating different machine learning models for classifying fake news. The dataset used for this evaluation consists of labeled news articles as either "REAL" or "FAKE". Three popular classifiers, Support Vector Machine (SVM), Decision Tree, and Logistic Regression, are trained and evaluated on this dataset.

Data Science Assignment Module 2 (K-Fold Cross Validation)

This repository contains mini projects inData science in python with notebook files

This project implements a Convolutional Neural Network (CNN) to recognize handwritten digits from the MNIST dataset using PyTorch.

Binary classification and Multiclass classification with pipelining and parameter tuning with GridsearchCV and RandomizedSearchCV

Building a model to predict demand of shared bikes. It will be used by the management to understand how exactly the demands vary with different features. They can accordingly manipulate the business strategy to meet the demand levels.

I developed the model to attain the predictive analysis in this task.

Training a model to predict whether a given job posting is fake or not

This is a machine learning model built in python3 to predict transaction conversion of web visits for an e-commerce website.

This repository serves as a comprehensive resource for understanding and implementing various feature selection techniques, gaining familiarity with Jupyter Notebook, and mastering the process of model training and evaluation

A web application that employs machine learning models to provide accurate and instant car price estimations based on various features and specifications.