Merve Acar
Verified Expert in Engineering
数据科学家和软件开发人员
Merve is an experienced machine learning engineer who takes pleasure in revealing the story of data and building predictive models with a proven track record of designing and implementing pipelines for extracting, validating, cleaning, transforming, 建模数据. She is passionate about solving real-world industry problems and eager to take on new challenges and opportunities.
Portfolio
Experience
Availability
首选的环境
Git, PyCharm, Jupyter Notebook, Linux, Windows, Amazon EC2, Jira, Slack
最神奇的...
...automated machine learning tool I've developed leverages the meta-learning power to select the most optimal algorithm and its parameters, 适应任何任务.
Work Experience
Data Analyst
Trust & 安全实验室
- Automated the collection of social media accounts spreading misinformation from multiple fact-check sites.
- Utilized Hugging Face's CLIP model for zero-shot learning to detect harmful content in images.
- Performed analyses to visualize bad actors and their friends of friends network graphs.
- 将客户需求转换为Tableau中的交互式仪表板.
Data Scientist
土耳其航空航天工业
- Developed a dashboard-based surveillance system to improve a factory's work processes using IP camera recordings. Applied video and image processing algorithms using the OpenCV library together with object detection and object tracking algorithms.
- Built an LSTM-based model to identify people's actions and improve work processes in a factory.
- Developed a predictive maintenance model using ARIMA and LSTM algorithms which provides insight into a plane part's breakdown using the time-series data of a plane component. 应用数据操作、分析和可视化.
机器学习工程师
维达斯大宗商品
- 使用Selenium参与了几个数据抓取项目, API calls, 请求库, and more.
- 在Microsoft Power BI上创建报告以实现数据可视化.
- Implemented a multilayer perceptron model using Python and Keras to forecast the natural gas demand in the UK for the coming days.
- Deployed an LSTM model that predicts Turkey's electricity price for the next few days.
- Implemented a scraper to obtain and manipulate GFS weather data to use as a source for model training.
- Investigated deep learning methods to enhance the performances of the current working models for time-series data.
- Implemented an outlier detection project consisting of probabilistic and clustering-based algorithms and an autoencoder method to detect extreme days concerning the UK's natural gas demand.
机器学习工程师
Independent Work
- 实现的数据预处理, data imputation, 特征提取, 以及使用Scala的Vitriol项目的模型创建模块.
- Researched and tested a meta-learning strategy to predict the best model with the best parameters for a given problem using Scala and Spark.
- Implemented a parser to handle unstructured data that comes from different sources using Python.
- 使用Apache Spark框架和Scala处理大数据.
软件开发人员
C3S命令控制 & 控制论系统
- Developed connector reliability testing software that controls the connection between PCI cards and connectors on the Linux platform.
- Built software that calculates how much time an employee spends at the office.
- 编写SQL数据库查询，分析员工的工作日程.
软件测试开发人员
Taleworlds娱乐
- 为Mount开发了自动化测试&Blade: Bannerlord II项目.
- Monitored test results and reported bugs found in prerelease software on a daily basis.
- Performed unit tests and integration tests to determine if the game scenes were working correctly.
- 在敏捷环境中与多个团队一起工作.
软件开发人员
TUBITAK |土耳其科学技术研究委员会
- 为Pardus开发了一个家长控制工具, 一个由土耳其政府支持的Linux发行版.
- 实现了内容过滤、使用控制和监视模块.
- 获得了开源开发和安全领域的经验.
Experience
Vitriol
http://senior.ceng.metu.edu.tr/2016/mallorn/I used a meta-learning strategy to select the most appropriate algorithm and its parameters. This project is implemented in Spark and the Scala programming language to handle big data.
天然气需求预测
First, I implemented an extreme day detection module to label the data as extreme or not extreme. An oversampling method helped enhance extreme days because they were a small portion of the data. I also implemented a dynamic weighted ensemble model using a multilayer perceptron (MLP) and a linear regression model to consider both linear and non-linear trends.
股价预测
图像去噪
PriceTag
Pardus Gozcu
Skills
Languages
Python, SQL, Python 3, Bash, Scala, C++, Haskell, Bash Script, R, XML, Snowflake
Libraries/APIs
Matplotlib, Scikit-learn, Pandas, PyTorch, Keras, Slack API, XGBoost, OpenCV, 自然语言工具包(NLTK), Spark ML, PyQt, Beautiful Soup, TensorFlow, Protobuf, Twitter API, NetworkX
Tools
Microsoft Power BI, PyCharm, Slack, Git, Seaborn, Plotly, Tableau, Jira, Bazel, 你只看一次(YOLO)
Paradigms
Data Science
Other
机器学习, 预测建模, Data Processing, Web Scraping, 谷歌合作实验室(Colab), Regression, Classification, Decision Trees, 人工智能(AI), CSV, 探索性数据分析, Data Cleaning, Computer Vision, Metric Learning, Time Series, Data Mining, Visualization, Deep Learning, Statistics, Object Detection, Object Tracking, 时间序列分析, 数据可视化, 软件工程, 卷积神经网络(CNN), Image Analysis, Neural Networks, Data Structures, Data Analysis, Data Modeling, 版本控制系统, Models, Modeling, Communication, Data Analytics, APIs, Data, 无监督学习, 监督式机器学习, 决策建模, 数据驱动的决策, Data Engineering, Dashboards, Reports, Data Scientist, 统计分析, Remote Sensing, 自然语言处理(NLP), Cloud Services, Design, 机器学习自动化, 门控循环单元(GRU), 生成对抗网络(GANs), 长短期记忆(LSTM), Data Scraping, Feature Analysis, Amazon RDS, 情绪分析, GPT, 生成预训练变压器(GPT), Okta, OpenAI GPT-3 API
Frameworks
Selenium, Spark
Platforms
Windows, Linux, Jupyter Notebook, RapidMiner, Amazon EC2, 亚马逊网络服务(AWS), Gephi, AWS Lambda
Storage
PostgreSQL, MySQL, Data Pipelines, Databases, Amazon S3 (AWS S3), JSON
Education
计算机工程硕士学位
伊斯坦布尔技术大学-伊斯坦布尔，土耳其
计算机工程学士学位
中东技术大学-安卡拉，土耳其
Certifications
使用Python访问Web数据
Coursera
构建机器学习项目
Coursera
卷积神经网络
Coursera
实用时间序列分析
Coursera
可视化的基础与Tableau
Coursera
谷歌云平台大数据和机器学习基础
Coursera
神经网络和深度学习
Coursera
机器学习基础:案例研究方法
Coursera
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