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ab_testing

Facebook kısa süre önce mevcut "maximum bidding" adı verilen teklif verme türüne alternatif olarak yeni bir teklif türü olan "average bidding"’i tanıttı. Müşterilerimiz bu yeni özelliği test etmeye karar verdi ve average bidding'in maximum bidding'den daha fazla dönüşüm getirip getirmediğini anlamak için bir A/B testi yapmak istiyor

amazon_sorting_reviews

Our aim in this task is to score the given points according to the date. evaluate by weight.

artificial_neural_network

In this project, we will build a neural network to classify dates. We'll use the “Date Fruit Dataset” available on Kaggle for this. This dataset includes samples of dates that can be classified into 7 classes according to their types.

association_rule_learning

Association Rule Learning project on online_retail_II dataset, you can read the readme file for the details of the project. You can find the link of the dataset in the codes.

atakankizilyuce

cat_dog_classification

Cat and Dog Classification using Keras

classification_example

In this dataset, we considered patients with and without cancer. We converted it to numeric data with label encoder and trained a model with the data we converted.

convolutional_neural_network

In this project, we will build a convolutional neural network to solve a multiclass image classification problem. For this, we'll use the “CIFAR-10” dataset available on Keras. It includes 60000 32 by 32 images of 10 classes.

data-analysis

✨ Real-life Data Analysis and Model Training Workshop by Global AI Hub.

eksik_veriler

eksikveriler.csv dosyası üzerindeki eksik verilerin yas kolonundaki verilerin ortalaması alınarak doldurulması

flo_cltv_and_segmentation

CLTV Prediction with BG-NBD and Gamma-Gamma and customer segmentation (RFM)

gaih-machine_learning_project

gaih_pybtcmp-29

heart_cleveland_model

In this project, we worked on the "heart_cleveland" dataset, since all the data in the dataset are numerical, we did not convert any categorical data to numerical data. We compared the performances of 2 models in the project and determined the model with the highest score.

image-captioning-keras

Converting the content of an image to text using cnn and transformer I will be using the Flickr8K dataset for this project. This dataset comprises over 8,000 images, that are each paired with five different captions. Example: image,caption - 1000268201_693b08cb0e.jpg,A child in a pink dress is climbing up a set of stairs in an entry way.

image_segmentation_keras-unet

A simple program that segments objects in the picture with the keras unet model. You can find dataset and model in notebook

iou-python

I would like to share with you an iou function that you can integrate into your programs. To integrate it into your program, simply enter the "box1" and "box2" values as x1,y1,x2,y2.

javahastaneotomasyonu

Görsel programlama ile Java dilinde kodlanmış hastane otomasyonu

kaggle-titanic-solution

Kaggle Titanic Solution

kerasvsyolo

I have developed a program that allows you to see your Keras and YOLO results on a single photo on the project you are working on. This way you can save a lot of time. I briefly showed how to use the program in the video. For more information use README file

knn_example

KNN (K-Nearest Neighbor) example, In short for KNN: We can say that the predictions are made according to the similarity of the observations. In this example, we did a KNN model setup, estimation, and model tuning. What are the KNN Steps? KNN Steps: 1-Determining the number of neighbors 2-Calculation of the distance between the unknown point and all other points 3-Sort the distances and select the closest k observations according to the determined k number 4-Classification, on the other hand, is most often given as the predictive value of the class, while the mean value of the regression is given as the predictive value.

makine-ogrenmesi-turkce

Makine öğrenmesi ve Derin öğrenme hakkında bulduğum Türkçe kaynaklar.

netflix_data_analytics

One of the projects I developed for Python Bootcamp organized by Global Ai Hub. I used data analysis and data visualization while developing the project. Dataset=(https://www.kaggle.com/datasets/luiscorter/netflix-original-films-imdb-scores)

recommendation-systems

Association Rule Learning, Content Based Recommendation, Item Based Collaborative, Filtering User Based Collaborative Filtering, Model Based Matrix Factorization projects i've done about

regression_example

The predictions we make in the regression are often wrong. What matters to us is how wrong these estimates are. In this study, we used RMSE to find the error rate. We used correlation to see the linear relationship between two variables

rfm_analysis

RFM analysis and customer segmentation with the data of an e-commerce site

time_series

yolov5_blood_cell_detection

This notebook shows training on the Blood Cell Dataset (BCCD). This technologoy will become easily accessible to any developer wishing to use computer vision in their projects.