Pinned Repositories
advanced-hyperparameter-optimization-techniques
HalvingGridSearch, HalvingRandomSearch, Bayesian Optimization, Keras Tuner, Hyperband optimization
automate-web-scraping-send-whatsapp-alert-with-aws
Scraping Azerbaijani real estate website and sending whatsapp message with AWS Lambda function that automatically triggered by Amazon CloudWatch.
azcorpus_v0
azcorpus - The largest NLP corpus for Azerbaijani (1.9M documents, ~ 18M sentences)
AzVoiceSent
AzVoiceSent is research project focused on sentiment classification from voice transcriptions in Azerbaijani. The project has the potential to provide valuable insights into the sentiment expressed by speakers in various domains and applications.
Easy-Recipes-bot
This telegram bot will find easy recipes in Azerbaijani using ingredients you already have in the kitchen.
image_to_handwriting_az
This project allows you to convert image into Azerbaijani handwriting
mgpt-az-streamlit
This project is a Streamlit app that uses the mGPT-XL (1.3B) model to generate Azerbaijani text. Users can input partial text, and the model will complete it with contextually relevant text in Azerbaijani.
New-product-demand-forecasting-via-Content-based-learning-for-multi-branch-stores
New product demand forecasting via Content based learning for multi-branch stores: Ali and Nino Use Case
Norvig-s-Spell-Checker-Algorithm-for-Azerbaijani-Language
The purpose of this project is to prepare a spell checker for Azerbaijani language by implementing a Azerbaijani corpus to Norvig’s algorithm. The corpus I created consists of 1478667 words collected from 47 books in 6 fields (biology, geography, detective, literature, encyclopedia, novel)
Satellite-images-to-real-maps-with-Deep-Learning
In this project, I developed a Pix2Pix generative adversarial network for image-to-image translation. I have used the so-called maps dataset used in the Pix2Pix paper.
NijatZeynalov's Repositories
NijatZeynalov/Satellite-images-to-real-maps-with-Deep-Learning
In this project, I developed a Pix2Pix generative adversarial network for image-to-image translation. I have used the so-called maps dataset used in the Pix2Pix paper.
NijatZeynalov/New-product-demand-forecasting-via-Content-based-learning-for-multi-branch-stores
New product demand forecasting via Content based learning for multi-branch stores: Ali and Nino Use Case
NijatZeynalov/automate-web-scraping-send-whatsapp-alert-with-aws
Scraping Azerbaijani real estate website and sending whatsapp message with AWS Lambda function that automatically triggered by Amazon CloudWatch.
NijatZeynalov/Norvig-s-Spell-Checker-Algorithm-for-Azerbaijani-Language
The purpose of this project is to prepare a spell checker for Azerbaijani language by implementing a Azerbaijani corpus to Norvig’s algorithm. The corpus I created consists of 1478667 words collected from 47 books in 6 fields (biology, geography, detective, literature, encyclopedia, novel)
NijatZeynalov/advanced-hyperparameter-optimization-techniques
HalvingGridSearch, HalvingRandomSearch, Bayesian Optimization, Keras Tuner, Hyperband optimization
NijatZeynalov/Easy-Recipes-bot
This telegram bot will find easy recipes in Azerbaijani using ingredients you already have in the kitchen.
NijatZeynalov/Predict-House-Price-using-ANNs
Predicting House price using Artificial Neural Networks
NijatZeynalov/Scraper-Chatbot
Scraper chatbot which answer more than a half bilion questions.
NijatZeynalov/concept-drift-adversarial-validation
In the project, I have detected concept drift by using adversarial validation and Kolmogorov-Smirnov test which can also be used in the deployed system.
NijatZeynalov/Detecting-Weapon-objects-by-using-RetinaNet-model-with-TensorFlow
I have used Object Detection API and retrain RetinaNet model to spot weapon objects using just 4 training images.
NijatZeynalov/Generate-Synthetic-Images-with-DCGANs-in-Keras
Generate images of clothing items by using Deep Convolutional Generative Adversarial Networks (DCGANs)
NijatZeynalov/Azerbaijani-Fake-News-Generator
The aim of this project is to generate fake news in the Azerbaijani language using LSTM Recurrent Neural Networks. LSTM Recurrent Neural Networks are powerful Deep Learning models which are used for learning sequenced data. Here a LSTM model was trained on 65 thousand samples, and it should be able to generate text.
NijatZeynalov/azerbaijani-medical-question-classification
Azerbaijani Medical Forum Question Classification
NijatZeynalov/Building-Neural-Network-architectures-from-scratch
I have built simple versions of some Neural Network architectures (Alexnet, Inception-v1, Resnet-18, Vgg-16) from scratch by using TensorFlow.
NijatZeynalov/Cleaning-Text-NLTK
Cleaning Text Manually and with NLTK.
NijatZeynalov/DEEP-LEARNING-FOR-SENTIMENT-ANALYSIS-ON-REVIEWS-OF-MODERN-AZERBAIJANI-MOVIES
The paper mainly describes the implementation of the Multilayer Perceptron (MLP) model - that can be used to detect sentiments from the text.
NijatZeynalov/Ensemble-Learning-Algorithms
Ensemble models in machine learning combine the decisions from multiple models to improve the overall performance
NijatZeynalov/handling-imbalanced-data
An imbalanced classification problem is a problem that involves predicting a class label where the distribution of class labels in the training dataset is not equal.
NijatZeynalov/IMDB-Sentiment-Analysis
Sentiment Analysis using Recurrent Neural Network on 50,000 Movie Reviews Compiled from the IMDB Dataset
NijatZeynalov/optuna-hyperparameter-optimization
Optuna is an open-source hyperparameter optimization framework to automate hyperparameter search. The key features of Optuna include automated search for optimal hyperparameters, efficiently search large spaces and prune unpromising trials for faster results, and parallelize hyperparameter searches over multiple threads or processes.
NijatZeynalov/Scraping-Rotten-Tomatoes
In this notebook, I have used scraping method for movies in the "Rotten Tomatoes" website. This project based on "Web Scraping and API Fundamentals in Python" course of 365 Data Science.
NijatZeynalov/Tensorflow-MNIST-Exercises
These exercises are prepared by 365datascience.com for the "Deep Learning with TensorFlow 2.0" course. Exercises are based on MNIST dataset and consist of several main adjustments for trying and practicing Tensorflow.
NijatZeynalov/Advanced-eXtreme-Gradient-Boosting-with-Python
Developing, evaluating and monitoring popular XGBoost model.
NijatZeynalov/azerbaijani-multi-news-dataset
Azerbaijani News Summary Dataset
NijatZeynalov/Fuel-consumption-of-vehicles
Estimating real-world fuel consumption of vehicles using the multiple machine learning methods
NijatZeynalov/mobile-phone-classification-keras
In this notebook, I will make my first neural network(ANN) using keras framework. The data is about mobile phones of various companies and consist of features of a mobile phone(eg:- RAM,Internal Memory etc) and its selling price.
NijatZeynalov/Neural-Machine-Translation-Model
Developing a Neural Machine Translation Model (Azerbaijani - English)
NijatZeynalov/Opening-New-Restaurant-in-Baku
Opening a New Restaurant in Baku, Azerbaijan
NijatZeynalov/Scikit-Optimize-Bayesian-Hyperparameter-Optimization
Scikit Optimize implements several methods for sequential model-based optimization. The library is very easy to use and provides a general toolkit for Bayesian optimization that can be used for hyperparameter tuning. It also provides support for tuning the hyperparameters of machine learning algorithms offered by the scikit-learn library.
NijatZeynalov/Whole-or-Damaged-car
Convolutional Neural Network with a custom architecture used for binary classification of images. The model predicts whether the car is a whole or a damaged.