-gesture-based-computer-controlling-using-arduino

In this project, we have successfully demonstrated how to control a computer using hand gestures with the help of an Arduino board. By using a combination of an ultrasonic sensor and a microcontroller, we were able to capture hand gestures and convert them into specific commands for the computer.

10th-order-fir-filter

In this Digital Systems Designing semester project, we will be designing 10th order finite impulse response (FIR). The FIR filter is widely used in digital communication and control systems.

4-bit-comparator-using-2-bit-comparator-verilog-code

A Comparator is a combinational circuit that gives output in terms of A>B, A<B, and A=B. This is entirely expected from the name. A digital comparator’s purpose is to compare numbers and represent their relationship with each other.

arduino-and-esp8266-projects

This repository is containing some basic projects code related to Arduino and ESP8266. Can be helpful for the new learners.

bigmart-mini-project

The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim of this data science project is to build a predictive model and find out the sales of each product at a particular store. Using this model, BigMart will try to understand the properties of products and stores which play a key role in increasing sales. The data has missing values as some stores do not report all the data due to technical glitches. Hence, it will be required to treat them accordingly.

data-cleaning-course-on-kaggle

Data cleaning is a key part of data science, but it can be deeply frustrating. Why are some of your text fields garbled? What should you do about those missing values? Why aren’t your dates formatted correctly? How can you quickly clean up inconsistent data entry? In this course, you'll learn why you've run into these problems and, more importantly, how to fix them! In this course, you’ll learn how to tackle some of the most common data cleaning problems so you can get to actually analyzing your data faster. You’ll work through five hands-on exercises with real, messy data and answer some of your most commonly-asked data cleaning questions.

data-visualization

Welcome to Data Visualization! In this hands-on course, you'll learn how to take your data visualizations to the next level with seaborn, a powerful but easy-to-use data visualization tool. To use seaborn, you'll also learn a bit about how to write code in Python, a popular programming language.

deep-learning-with-pytorch-image-segmentation

Understand the Segmentation Dataset and you will write a custom dataset class for Image-mask dataset. Additionally, you will apply segmentation augmentation to augment images as well as its masks. For image-mask augmentation you will use albumentation library. You will plot the image-Mask pair. Load a pretrained state of the art convolutional neural network for segmentation problem(for e.g, Unet) using segmentation model pytorch library. Create train function and evaluator function which will helpful to write training loop. Moreover, you will use training loop to train the model.

electronic-voting-machine-evm-using-8051-microcontroller-project

Electronic Voting Machine(EVM) is a simple electronic device used to record votes in place of ballot papers and boxes which were used earlier in conventional voting system. Fundamental right to vote or simply voting in elections forms the basis of democracy. All earlier elections be it state elections or centre elections a voter used to cast his/her favorite candidate by putting the stamp against his/her name and then folding the ballot paper as per a prescribed method before putting it in the Ballot Box. This is a long, time-consuming process and very much prone to errors. This situation continued till election scene was completely changed by electronic voting machine. No more ballot paper, ballot boxes, stamping, etc.

first-contributions

🚀✨ Help beginners to contribute to open source projects

google-dsc-platform-extension

Hello DSC Leads, Automate your process of adding attendees manually.

hacktoberfest

Make your first PR! ~ A beginner friendly repository made specifically for open source beginners. Add any program under any language (it can be anything from a hello-world program to a complex data structure algorithm) or update the existing one. Just make sure you add the program under the correct language directory. Happy coding

hacktoberfest-22

A beginner friendly repository made specifically for open source beginners for Hacktoberfest. Add any program under any language (it can be anything from a hello-world program to a complex data structure algorithm) or update the existing one. Just make sure you add the program under the correct language directory.

hacktoberfest2021

Submit Just 4 PRs to earn SWAGS and Tshirts🔥

hacktoberfest2022

Hacktoberfest 2022 OPEN FIRST Pull Request - FREE T-SHIRT🎉

iammkullah

Config files for my GitHub profile.

iammkullah-implementation-of-16-bit-adder-project

It was based on a ripple carry adder where two 4-bit ripples carry adders and a multiplexer forms the basic building block.

image-classification-with-tensorflow

we will build a neural network model to solve a basic image classification problem

introduction-to-tensorflow-for-artificial-intelligence-machine-learning-and-deep-learning-solution

In this repository I am providing the solution for the cousera course "Introduction-to-TensorFlow-for-Artificial-Intelligence-Machine-Learning-and-Deep-Learning". Following is the description of the course. If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

investigating-netflix-movies-and-guest-stars-in-the-office

Our friend has also been brushing up on their Python skills and has taken a first crack at a CSV file containing Netflix data. For their first order of business, they have been performing some analyses, and they believe that the average duration of movies has been declining.

jack-of-many-trades

This repository is dedicted to participate in HECKTOBERFEST 2022. By participating to this repository you will be helping many people from different domains.

learning-django-2825501

Learning Django (REVISION)

machine-learning---intro-and-intermediate

We'll start with an overview of how machine learning models work and how they are used. This may feel basic if you've done statistical modeling or machine learning before.

markdown-cheatsheet

Markdown Cheatsheet for Github Readme.md

muhammad-bilal-mb

Config files for my GitHub profile.

object-localization-with-tensorflow

Welcome to this 2 hour long guided project on creating and training an Object Localization model with TensorFlow. In this guided project, we are going to use TensorFlow's Keras API to create a convolutional neural network which will be trained to classify as well as localize emojis in images. Localization, in this context, means the position of the emojis in the images. This means that the network will have one input and two outputs. Think of this task as a simpler version of Object Detection. In Object Detection, we might have multiple objects in the input images, and an object detection model predicts the classes as well as bounding boxes for all of those objects. In Object Localization, we are working with the assumption that there is just one object in any given image, and our CNN model will classify and localize that object. Please note that you will need prior programming experience in Python. You will also need familiarity with TensorFlow. This is a practical, hands on guided project for learners who already have theoretical understanding of Neural Networks, Convolutional Neural Networks, and optimization algorithms like Gradient Descent but want to understand how to use use TensorFlow to solve computer vision tasks like Object Localization.

pandas

In this micro-course, you'll learn all about pandas, the most popular Python library for data analysis.

product-sales-outlet-at-bigmart-datawarehouse

he data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim of this data science project is to build a predictive model and find out the sales of each product at a particular store.

project-fidget-spinner-3d-model-autocad

This repository will provide you the overview about the 3D modal of the fidget spinner. A fidget spinner is a toy that consists of a ball bearing in the center of a multi-lobed (typically two or three) flat structure made from metal or plastic designed to spin along its axis with very little effort. A person holds the center pad while the toy spins. They are made from various materials including brass, stainless steel, titanium, copper, aluminum, and plastic. The software we used for the model is AutoCAD. The objectives of the project are (1) to get familiar with the 3D interference of the AutoCAD, (2) to increase the productivity of the designer, (3) to improve the quality of design. Following are the 3 main things we follow to create our desire model of fidget spinner.

python-scraping-projects