IPL Case Study
Description:
I was given a dataset and wanted to draw insights about the the best team in tournament. Apart from this I created dashboard having graph for best team and best player in the tournament.
Posted:
Artificial Intelligence
Get the most out of your training, scoring, algorithms and frameworks on Intel® architecture for Deep Learning and Artificial Intelligence.
StayCatin Listing
Description:
I need to come up with a dashboard that helps management answer the key questions: 1. Top 10 earners 2. Relationship between price and earnings 3. Any location (shore) getting more earnings 4. Relationship between price and reviews
Posted:
Movie Reccomendor System
URL: https://sahilgupta0712-movie-recommender-app-g8qhcb.streamlitapp.com/
Description:
A movie recommendation system, or a movie recommender system, is a ML-based approach to filtering or predicting the user's film preferences based on the movie or the genre they choose. The primary goal of movie recommendation systems is to filter and predict only those movies that a corresponding us
Posted:
Exhibition Art - Shipping Cost Predictor
URL: https://github.com/deepakjoshi2k/Machine-Learning-Exhibit-Art-Shipping-
Description:
My project is the complete analysis of the data of a Shipping Company. The main aim is to predict the cost of shipping provided the required entries were given but along with the EDA, it becomes much more than just the Cost Predictor.
Posted:
Movie Recommender
URL: https://github.com/kunal9718/Movie-Recommender
Description:
Its a movie recommendation system which will recommend the movies based on genre and movie type.
Posted:
Performance and Portability Evaluation of the K-Means Algorithm on SYCL with CPU-GPU architectures
URL: https://github.com/artecs-group/k-means
Description:
This work uses the k-means algorithm to asses the performance portability of one of the most advanced implementations of the literature, He-Vialle, over different programming models (DPC++, CUDA, OpenMP) and multi-vendor CPU-GPU architectures.
Posted:
Deploying Machine Learning models for SpaceY who wants to bid against SpaceX
Description:
In this, we deployed different ML models for a company SpaceY that wants to bid against SpaceX. We have collected data regarding successful landings of SpaceX from SpaceX's public API and Wikipedia page. Then we have produces 4 ML models, which produced similar results of accuracy of about 83.33%.
Posted:
Modin gives Pandas wings
URL: https://www.kaggle.com/code/rishirajacharya/oneapi-modin-gives-pandas-wings
Description:
An element of the oneAPI AI Analytics toolbox is Intel® Distribution of Modin. With little any work, you can scale data analytics and speed up your current Pandas code. Learn how to run the same Pandas code 10, 20, or 30 times quicker.
Posted:
Answer sheet Assessment and Checking: oneAPI Deep Neural Network Project
Description:
Project on making a system using oneAPI Deep Neural Network Library to check and assess the answer sheets of thousands of candidates for various tests for organizations using ML/DL techniques Dataset: with the help of the MNIST dataset
Posted:
Novel Applications of Transformer Models in Data Interpretation and Visualization
URL: https://github.com/andreicozma1/oneAPI-viz
Description:
This project explores the possibilities of using attention-based transformer models to aid in tasks related to data visualization and interpretation, through the use of various Intel oneAPI toolkits such as the DNN library, oneAPI AI Kit, as well as oneAPI Render Kit.
Posted:
Acceleration of Kalman Filter applications on GPUs and FPGAs.
URL: https://github.com/menotti/Kalman-Filter-for-Beginners/
Description:
The objective of this project is to accelerate implementations of the Kalman filter for various purposes, including the calculation of drone attitude.
Posted:
Image Depth Masking
URL: https://github.com/NicholasSynovic/image-depth-masking
Description:
Using the Intel MiDaS model, estimate the depth of an image and mask parts of the image that are at a specific depth value.
Posted:
RISK IDENTIFICATION IN PREDICTIVE ESTIMATION
URL: https://github.com/QuanticTechnovations/OneAPI_RiskAnalyzer
Description:
Significant business decisions is taken based on the outcome predicted by the ML model. Users get benefit from an unbiased, statistically sound and rigorous re-validation of the prediction’s accuracy from an independent source. That is what the Predictive Risk Analyzer tool from Quantic aims to go.
Posted:
Credit Card Fraud Detection Using Machine Learning & Data Science
Description:
I Have Developed An Algorithm Which Detects Credit Card Frauds In 8 Seconds And Alerts Blank Servers To Block The Transactions I Have Used R-Language To Develop The Algorithm And R-Studio As IDE Also I Have Used Data Set Which Was Available On Kaggle I Have Provided My Git-Hub Profile Link Were You
Posted:
Credit Card Fraud Detection Using Machine Learning & Data Science
Description:
I Have Developed An Algorithm Which Detects Credit Card Frauds In 8 Seconds And Alerts Blank Servers To Block The Transactions I Have Used R-Language To Develop The Algorithm And R-Studio As IDE Also I Have Used Data Set Which Was Available On Kaggle I Have Provided My Git-Hub Profile Link Were You
Posted:
Hierarchy of binary classifiers for multiclass classification
URL: https://www.kaggle.com/code/mohit12562/hierarchy-of-binary-classifiers
Description:
For a multiclass classification task, the idea behind using hierarchy of binary classifiers is that the set of classes in training data has similar number of examples for a pair of groups of classes.
Posted:
DeciSym.AI Engine
URL: https://github.com/DeciSym
Description:
DeciSym.AI Engine is a triple store database tuned for HPC and Cloud Computing deployments of AI/ML workflows.
Posted:
Unity Mujoco with Intel Xe Graphics
Description:
we will see how we implement the Unity Mujoco plugin to create a scene rendered with Intel Xe Graphics.
Posted:
Virtual Construction Inspector
URL: https://github.com/cabelo/VirConI
Description:
Personal Protective Equipment (PPE) Detector
Posted:
DREAMPlaceFPGA
URL: https://github.com/rachelselinar/DREAMPlaceFPGA
Description:
This work aims to accelerate the different stages involved in FPGA placement - global placement, legalization and detailed placement, using the Pytorch deep-learning toolkit. Placement in the FPGA design flow determines the physical locations of all the heterogeneous instances in the design.
Posted: