module

I am sharing my own module. The codes will be added based on my own ML Workflow. For the ML Workflow link: https://bunyaminergen.notion.site/ML-WORKFLOW-7866bc6d88d44315a6521ead9e89d857 for more inform please jump to README.md

mongo-db--apache-kafka--spark-streaming---visualizations-

Details in Specifications

monk_v1

Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.

movie-recommendation-system-with-python

Basic recommendation system by suggesting movies that are most similar to a particular movie.

mplfinance

Financial Markets Data Visualization using Matplotlib

multi-class-with-imbalanced-dataset-classification

Multi-class with imbalanced dataset classification

naip-multispectral-imagery

Using multispectral imagery from NAIP in agriculture

ndvi-forcasting-sugarcane-plantations

A project to forecast ndvi values of sugarcane plantations as an indicator of crop performance/health using satellite images from sentinel 2

ndvi-time-series-analysis

Analysis of satellite images/NDVI images to obtain sowing and harvesting periods of crops in a region of interest.

neural-garch-hybrid-model-implementation

By combining GARCH(1,1) and LSTM model implementing predictions.

newsrecommender

A news recommendation system tailored for user communities

nlp-twittertweets-classifier

object-counter-using-opencv-instance-segmentation

Object Counter using Opencv Instance Segmentation - Mask R-CNN

openai-medical-text-to-dataframe

Medical Text Extraction

opencv-python-tutorials

Code for my laerning of OpenCV Python Tutorials

optimized-parameter-tuning-with-gridsearchcv

outfit

:dress: Tidy up your machine learning experiments

papel.sol

safemoon contract

photomosaic-generator

photomosaic generator (image to image, video to video)

pipeline-examples

planning-multi-robot-gym

A Gymnasium environment for simulating multi-robot planning.

plant-health-identification-using-leaf-images-cnn-and-ndvi-

poincare-embeddings

PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"

poincaremaps

The need to understand cell developmental processes has spawned a plethora of computational methods for discovering hierarchies from scRNAseq data. However, existing techniques are based on Euclidean geometry which is not an optimal choice for modeling complex cell trajectories with multiple branches. To overcome this fundamental representation issue we propose Poincaré maps, a method harnessing the power of hyperbolic geometry into the realm of single-cell data analysis.

portfolio_2

practicalai

📚 A practical approach to learning and using machine learning.

predict-african-soil-property

Africa Soil Property Prediction Challenge in Kaggle

predictive-maintenance

Data Wrangling, EDA, Feature Engineering, Model Selection, Regression, Binary and Multi-class Classification (Python, scikit-learn)

prml

PRML algorithms implemented in Python

project