ErdeN Tüzünkan🌌

İstanbul, İstanbul, Türkiye İletişim Bilgileri
6 B takipçi 500+ bağlantı

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  • Verdiği hizmetler konusunda ErdeN Tüzünkan🌌 adlı kullanıcıyla iletişime geçin

    Yönetici Koçluğu, Topluluğa Karşı Konuşma, Kariyer Geliştirme Koçluğu, Hayat Koçu, Liderlik Gelişimi, Blogging ve Metin Yazarlığı

Hakkında

⚡️Turning the 20th work year, I’ve noticed a shocking truth:
💭I was lost at…

Katkılar

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Etkinlik

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Deneyim ve Eğitim

  • Healthy Office Habits

ErdeN Tüzünkan🌌 adlı kişinin tam deneyimin görüntüleyin

Unvan, işte kalma süresi ve daha fazlasını görün.

veya

Devam Et seçeneğini tıklayarak veya oturum açarak LinkedIn Kullanıcı Anlaşması’nı, Gizlilik Politikası’nı ve Çerez Politikası’nı kabul etmiş olursunuz.

Lisanslar ve Sertifikalar

Gönüllü Deneyimler

  • İstanbul Modern Grafik

    "Young Podium" University Art Program Coordinator

    İstanbul Modern

    - 1 yıl 6 ay

    Kültür ve Sanat

    ✍️ Coordinated the cooperation of university clubs with the museum under the program "Young Podium"

    📸 Hosted and organized many photograph exhibitions of young university students in Istanbul Modern

    👩‍🎓 Hosted and organized some of the Architectural School Juries of well-known universities under the roof of a museum, creating unforgettable and authentic memories.

  • TEGV - Türkiye Eğitim Gönüllüleri Vakfı Grafik

    "I am a human being, an individual, a citizen." Framework Educator Trainer

    TEGV - Türkiye Eğitim Gönüllüleri Vakfı

    - 7 yıl 2 ay

    Eğitim

    👩‍👧‍👦 The "I am a human being, an individual, a citizen." framework is a comprehensive Education Program about "Human Rights" targeting children 11-14 years old.

    🧠 I became an Educator Trainer for this magnificent "Human Rights Training".

    🙌During a 7 year span, I voluntarily educated more than 500 Volunteers including teachers, lawyers, university students, engineers, and doctors.

  • İKSV Grafik

    8th International Istanbul Biennial Artist's Assistant

    İKSV

    - 3 ay

    Kültür ve Sanat

    During the biennial, I worked as an Artist's Assistant for Araya Rasdjarmrearnsook.

    The 8th International Istanbul Biennial was held between 20 September – 16 November 2003 with the main theme "Poetic Justice"

  • TEGV - Türkiye Eğitim Gönüllüleri Vakfı Grafik

    I am a human being, an individual, a citizen." Framework Trainer

    TEGV - Türkiye Eğitim Gönüllüleri Vakfı

    - 4 yıl 9 ay

    İnsan Hakları

    👋 As an "I am a human being, an individual, a citizen." Framework Trainer, I facilitated dozens of semester-long "Human Rights" trainings for 11-14-year-old children.


    💖 One of the most fulfilling moments of my life...
    😇 Proud of...

  • JA Worldwide Grafik

    "Young Entrepreneurs" Program Trainer

    JA Worldwide

    - 2 yıl 11 ay

    Çocuklar

    🗣️ As a volunteer, I facilitated the "Young Entrepreneurs" Training Program supported by Citibank, TEGV, and JA Worldwide Turkey.

    💡 In TEGV's premises, me and one other Volunteer did accomplish the following steps with 6th graders
    → 15 6th Grade kids decided to form a fictive company during the course
    → They decided to focus on "Candle Production"
    → We calculated estimated costs and came up with a total budget
    → We issued the company shares and collected a small amount of…

    🗣️ As a volunteer, I facilitated the "Young Entrepreneurs" Training Program supported by Citibank, TEGV, and JA Worldwide Turkey.

    💡 In TEGV's premises, me and one other Volunteer did accomplish the following steps with 6th graders
    → 15 6th Grade kids decided to form a fictive company during the course
    → They decided to focus on "Candle Production"
    → We calculated estimated costs and came up with a total budget
    → We issued the company shares and collected a small amount of investment from each kid
    → Time for teams: Production team, Procurement team, finance team, sales team. Everybody was in action.
    → Designed a couple of sessions for candle production workshops: Colourful candles were designed and manufactured by the kids
    → Arranged a small desk opportunity in front of the company cafeteria of a crowded FMCG company during the launch break.
    → Kids managed to sell every piece they have created.
    → Time to distribute: Shareholders (Mothers and fathers :) to be exact) received their investments back.
    → Profits: There was a well-deserved profit. Kids (shareholders) decided collectively to donate their profits to TEGV premises. As far as I can remember, a coffee machine was bought and donated to TEGV's premises they have been using frequently.

  • TEGV - Türkiye Eğitim Gönüllüleri Vakfı Grafik

    Math Tutor

    TEGV - Türkiye Eğitim Gönüllüleri Vakfı

    - 10 yıl 7 ay

    Eğitim

    👨‍🏫 I voluntarily tutored 200+ kids from suburbs aged between 10 -14.
    🎲 Helped them to gain joy in math using gamification techniques.

Yayınlar

  • Staff Performance Scoring Using Machine Learning

    8th International Congress on Engineering and Technology Management

    Staff scoring is an important aspect of workflow resource management.

    Staff scoring is the computational process for decision-making to identify the appropriate workforce with the skills required to perform a particular task.
    With staff scoring, the assignment of appropriate work to appropriate staff is critical for the success of tasks. However, efficiency is low due to manual processing by management
    personnel. The aim of this study is to develop staff scoring models.
    For…

    Staff scoring is an important aspect of workflow resource management.

    Staff scoring is the computational process for decision-making to identify the appropriate workforce with the skills required to perform a particular task.
    With staff scoring, the assignment of appropriate work to appropriate staff is critical for the success of tasks. However, efficiency is low due to manual processing by management
    personnel. The aim of this study is to develop staff scoring models.
    For this purpose, machine learning-based Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Support Vector Machine (SVM) have been used with two different approaches to develop staff scoring models.
    Grid search has been used to find the optimal values of the hyperparameters of the mentioned methods.
    One-hot encoding and frequency enconding have been used separately to convert some features in the dataset.
    The data is collected from the customers and staff of AlbertSolino, and includes 9 features and 557 rows.

    10-fold cross-validation has been utilized along with confusion matrix and accuracy have been used to
    assess the performance of staff scoring models.

    It has been observed that the developed staff scoring models show consistent performance and can be used for measuring which task is more suitable for the staff.

    Yayını gör

  • Developing Customer Segmentation Models for Digital Marketing Campaigns using Machine Learning

    IMSEC 2021

    The ultimate goal of marketing is to earn more revenue and maintain profitability.
    This process may lead to wrong decisions if it’s not applied based on data and done manually.
    Due to our extensive management consulting background, it has been observed
    that it takes a very long time for many marketing activities to take action in the companies.
    Therefore, real-time decisions cannot be made on time and accurately.

    This study aims to provide a machine learning-based smart…

    The ultimate goal of marketing is to earn more revenue and maintain profitability.
    This process may lead to wrong decisions if it’s not applied based on data and done manually.
    Due to our extensive management consulting background, it has been observed
    that it takes a very long time for many marketing activities to take action in the companies.
    Therefore, real-time decisions cannot be made on time and accurately.

    This study aims to provide a machine learning-based smart digital marketing automation software
    that allows companies automatically customize the digital marketing campaigns according to customers’ interests and needs.

    Consequently, the software will act as a tool for a real-time management decision support system, increasing potential customers’ conversion rates to real customers and enabling cross-selling.
    For customer segmentation purposes, we created a dataset that includes information related to 64.543 campaign e-mails sent to potential customers from January 2018 to September 2019.

    By applying the Random Forest (RF), Gaussian Naïve Bayes (GaussianNB), k-Nearest Neighbor (kNN), and Logistic Regression (LogReg) classifiers on the dataset, models for classifying the campaign success have been developed.
    Using 10-fold cross-validation, various
    measures such as confusion matrix, precision, recall, and f1-score have been used to evaluate the performance of the models.
    The results show that RF, GaussianNB, and kNN produce comparable precision, recall, and f1-score values in classifying the digital campaign success.
    In contrast, LogReg exhibits unsatisfactory performance in terms of recall and f1-score values.

    Yayını gör

  • Smart Clothing Recommendation System with Deep Learning

    IEEE

    Recommendation systems based on machine learning are very important both customers and sellers in our daily life.
    Many recommendation systems need user's previous shopping activities and digital footprints to make best recommendation purpose for next item shopping. In this study, we develop a cloth recommendation system with using only single photo of user with scalable embedded system. This study lead to important results and give new opportunities for clothing companies and…

    Recommendation systems based on machine learning are very important both customers and sellers in our daily life.
    Many recommendation systems need user's previous shopping activities and digital footprints to make best recommendation purpose for next item shopping. In this study, we develop a cloth recommendation system with using only single photo of user with scalable embedded system. This study lead to important results and give new opportunities for clothing companies and advertisements.
    In this study, we show that how our system recommends a cloth options without user's previous shopping act data with embedded system and machine learning.

    In order to recommend a cloth, we develop two inception based convolutional neural networks as prediction part and one feed forward neural network as recommender.

    In this study, we reach to 98% accuracy on color prediction, 86% accuracy on gender and cloth's pattern predictions and 75% accuracy on clothing recommendation.

    Yayını gör

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  • Turkish

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