Syed Muqtasid Ali 's repositories
Personal-Chatbot
🤖 A Personal Chatbot built with Python and Natural Language Processing for fun and learning!
Fully-Connected-Dense-Layer
This project is about MNIST Handwritten Digit Single-Label Multi-class Classification problem (Densely Connected Network)
Human-Pose-Estimation
This repository contains code and models for human pose estimation, a computer vision task that involves predicting the positions of human joints (keypoints) in images or videos. The project leverages deep learning techniques to accurately detect and localize keypoints such as shoulders, elbows, knees, and ankles.
Digital-Image-Number-Detection
This Project is about just given the path of image that contain number project output will tell the number in picture.
PDF-and-Web-Data-Scraping-for-Machine-Learning
Python repository for machine learning, featuring PDF data extraction using PyMuPDF and web scraping with BeautifulSoup, integrated with pandas, numpy, and MySQL for streamlined data processing.
sales-forecasting
In this project, we aim to train a sales forecasting model using time series data. We'll be using a dataset sourced from Kaggle containing Advertising budget and Sales.
K-Means-Clustering
I have started with K values of 2 in which Image was divided into 2 clusters in which every color was according to the mean value of cluster 1 or cluster 2 and the final image was a result of only 2 colors image.
Hypothesis-Testing-and-Confidence-Intervals
Conduct hypothesis tests and calculate confidence intervals for the Heart Disease UCI dataset. The Heart Disease UCI dataset contains information about patients' health factors and whether they have heart disease or not. It includes attributes such as age, sex, cholesterol levels, blood pressure, and the presence of heart disease.
syedmuqtasidali
Here's a new dataset that you can use for building interactive visualizations and dashboards using Plotly: Dataset: "Netflix Movies and TV Shows"
Data-Manipulation-on-Iris-Flower-Dataset
Data manipulation and analysis using Pandas with the Iris flower dataset
fake-image-detection
Welcome to the Fake Image Detection project! This project aims to detect fake images using machine learning techniques. The project is implemented in a Jupyter Notebook
Web-Scrapping
Appliances Power Consumption Scrapper.first we scrape all power consumption data from Website and return all data in csv format.
neural-network-from-scratch
In the last lesson, we learned how to use gradient descent to train a linear regression algorithm. In this lesson, we'll build on this to make a multi layer neural network.
cancer-detection
In this project we are going to plot our cancer dataset in graph form and also find out precion,recall, accuracy and predictions.
Scrapping-Through-Web-Print
Web scraping tool utilizing a 'Print' button on web pages for streamlined data extraction.
KFUEIT-GPT
KFUEIT GPT is a project developed for the Final Year, leveraging the power of the MINI-LM-L6-V2 transformer library. This project integrates advanced technologies such as Flask, Python, and MySQL database to create an interactive query system.
hand-sign-language
Creating a Hand Sign Language Recognition project using Machine Learning and image processing techniques. The project leverages Convolutional Neural Networks (CNNs) for robust feature extraction from hand sign images. It involves extensive use of Python, TensorFlow, and OpenCV for image processing, model training, and real-time inference.
auto-visualization
Auto visualization tools provide a seamless way to gain insights from uploaded datasets by automatically generating visual representations of the data's key characteristics.
forward-neural-network
You are going to build a neural network for the image classification task. You will train the model on the diabetes prediction dataset.
segmentation
xploratory Data Analysis (EDA) for Customer Segmentation.DataGenius Analytics has been selected to conduct an exploratory data analysis (EDA) project that will help TechElectro Inc. discover meaningful patterns .
Resturant
Resturant Chatbot
Dynamic-Web-Scraping-Through-Menus
Web scraping is the process of extracting data from websites. It involves writing code to fetch web pages, parse their content, and extract specific information for further analysis or use.
COVID-19-World-Vaccination-Progress
Create visually appealing and informative visualizations for the COVID-19 World Vaccination Progress dataset and present key findings. The COVID-19 World Vaccination Progress dataset contains information about COVID-19 vaccination progress across different countries.
-Interactive-data-visualization-with-Plotly
Here's a new dataset that you can use for building interactive visualizations and dashboards using Plotly: Dataset: "Netflix Movies and TV Shows"
Task-1-Experimental-design-and-A-B-testing
Design and analyze A/B tests for a hypothetical scenario.
Explore-Dataset-By-Questions
Here are 20 data science questions that you can explore using your dataset of 300 students with columns for name, university, and CGPA:
Exploratory-Data-Analysis-EDA-
The Google Play Store Apps dataset contains information about various mobile apps available on the Google Play Store, including attributes like the app category, size, rating, reviews, and more. Your task is to perform exploratory data analysis to understand the characteristics and trends within the dataset and extract meaningful insights.
Perform-Exploratory-Data-Analysis-EDA-
The Google Play Store Apps dataset contains information about various mobile apps available on the Google Play Store, including attributes like the app category, size, rating, reviews, and more. Your task is to perform exploratory data analysis to understand the characteristics and trends within the dataset and extract meaningful insights.
Fundamentals-of-statistics-for-data-science
Here is a task for Task: Perform basic statistical calculations in Python using NumPy and SciPy, with a dataset:
gradient-descent-with-linear-regression
Gradient descent is a technique that helps us set the correct values for neural network parameters. Without gradient descent, networks wouldn't be able to learn how to make predictions from data.