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advance-deep-learning

Advanced Deep Learning repository! This repository is dedicated to exploring cutting-edge research, advanced techniques, and innovative applications in the field of deep learning. Our mission is to provide a comprehensive and accessible resource for students, researchers, and enthusiasts who are passionate about pushing the boundaries.

advanced-library-managment

Advanced Library Management Project using ADV Java & Advance Concepts of DBMS

ai-for-marketing

Marketing is crucial for the growth and sustainability of retail business. Marketers can help build the company’s brand, engage customers, grow revenue, and increase sales. AI can star change maker for Product Marketing & Business Boost

ai-ml-operations

Automating the end-to-end lifecycle of Machine Learning applications Machine Learning applications are becoming popular in our industry, however the process for developing, deploying, and continuously improving them is more complex compared to more traditional software, such as a web service or a mobile application. They are subject to change in three axis: the code itself, the model, and the data. Their behaviour is often complex and hard to predict, and they are harder to test, harder to explain, and harder to improve

ailia-models

The collection of pre-trained, state-of-the-art AI models for ailia SDK

aiops_project

AIOps is short for artificial intelligence for IT operations. It refers to multi-layered technology platforms that automate and enhance IT operations through analytics and machine learning (ML). AIOps platforms leverage big data, collecting a variety of data from various IT operations tools and devices in order to automatically spot and react to issues in real-time while still providing traditional historical analytics.

annotated_research_papers

This repo contains annotated research papers that I found really good and useful

applied-statistics-for-machine-learning-code-analysis-explanations

Statistics for Machine Leraning. From exploratory data analysis to designing hypothesis testing experiments, statistics play an integral role in solving problems across all major industries and domains.

augmennt

Augmentations for Neural Networks. Implementation of Torchvision's transforms using OpenCV and additional augmentations for super-resolution, restoration and image to image translation.

automate-vehicle-number-plate-recognition

Automatic number plate recognition (ANPR) is quickly becoming an increasingly popular solution offering organisations effective visitor and car park access management. Several trends and challenges are driving the popularity of this solution, such as increasing vehicle thefts, security concerns as well as the growing interest in smart parking solutions and automated vehicle identification. We are using Tensoflow based solution for ANPR

bike-rental-timeseries-forcasting-on-aws-deepar

The Amazon SageMaker DeepAR forecasting algorithm is a supervised learning algorithm for forecasting scalar (one-dimensional) time series using recurrent neural networks (RNN).When your dataset contains hundreds of related time series, DeepAR outperforms the standard ARIMA and ETS methods. You can also use the trained model to generate forecasts for new time series that are similar to the ones it has been trained on.

breast-cancer-prediction-using-image-procesisng

Each year number of deaths is increasing extremely because of breast cancer. It is the most frequent type of all cancers and the major cause of death in women worldwide. Any development for prediction and diagnosis of cancer disease is capital important for a healthy life. Consequently, high accuracy in cancer prediction is important to update the treatment aspect and the survivability standard of patients. Machine learning techniques can bring a large contribute on the process of prediction and early diagnosis of breast cancer, became a research hotspot and has been proved as a strong technique.

chase-pieces-object-detection-with-fasterrcnn-ssd-algorithm

cloudprojectgcp

Automatic number plate recognition (ANPR) is quickly becoming an increasingly popular solution offering organisations effective visitor and car park access management. Several trends and challenges are driving the popularity of this solution, such as increasing vehicle thefts, security concerns as well as the growing interest in smart parking solutions and automated vehicle identification. We are using GCP Cloud, Tensoflow based solution for ANPR

company_bankruptcy_prediction

composer-identification-reserach

computer-vision-work

cryptocurrency-price-prediction-using-arima-model

data-mining-

Data Mining all Assignments covering all types of different topics & their assignments with all needful details.

data-science-famework

This repository is a comprehensive collection of notebooks that covers various data science projects in detail. Each project is designed to provide a clear understanding of the data science pipeline, from data acquisition to model deployment.

deep-learning-model-for-song-prediction-form-huming-whistling

Building Audio Deep Learning Model for forecasting melody name. Sound Classification is one of the foremost broadly utilized applications in Audio Deep Learning. It includes learning to classify sounds and to anticipate the category of that sound. I am going begin with sound files, convert them into spectrograms, input them into a CNN plus Linear Classifier model, and create forecasts almost the lesson to which the melody has a place.

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

depthmapexplorer-3dpointcloudlab

Explore the World in 3D: 3DPointCloudLab is your gateway to the fascinating universe of 3D depth maps and point clouds. Whether you're a researcher, developer, or 3D enthusiast, our repository offers a treasure trove of tools, techniques, and insights dedicated to the exploration and manipulation of 3D spatial data.

detector-free-local-feature-matching-transformer-project

For most of us, our best camera is part of the phone in our pocket. We may take a snap of a landmark, like the Trevi Fountain in Rome, and share it with friends. By itself, that photo is two-dimensional and only includes the perspective of our shooting location. Of course, a lot of people have taken photos of that fountain. Together, we may be able to create a more complete, three-dimensional view. What if machine learning could help better capture the richness of the world using the vast amounts of unstructured image collections freely available on the internet? The process to reconstruct 3D objects and buildings from images is called Structure-from-Motion (SfM). Typically, these images are captured by skilled operators under controlled conditions, ensuring homogeneous, high-quality data. It is much more difficult to build 3D models from assorted images, given a wide variety of viewpoints, lighting and weather conditions, occlusions from people and vehicles, and even user-applied filters.

disaster-prediction-using-adv-nlp

disease-prediction-models

Disease prediction Models

dnyaneshwalwadkar

doremi

dvc-nlp-aiops-project

ecg-classifier

The electrocardiogram (ECG) signal basically corresponds to the electrical activity of the heart. In theliterature, the ECG signal has been analyzed and utilized for various purposes, such as measuring theheart rate, examining the rhythm of heartbeats, diagnosing heart abnormalities, emotion recognition andbiometric identification. ECG analysis (depending on the type of the analysis) can contain several steps,such as preprocessing, feature extraction, feature selection, feature transformation and classification.Performing each step is crucial for the sake of the related analysis. In addition, the employed successmeasures and appropriate constitution of the ECG signal database play important roles in the analysisas well.