Burcin Sarac,土耳其伊斯坦布尔的开发者
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Burcin Sarac

Verified Expert  in Engineering

数据科学家和软件开发人员

Location
Istanbul, Turkey
Toptal Member Since
August 13, 2021

Burcin是一位经验丰富的数据科学家和人工智能开发人员,拥有该领域的硕士学位,并获得了机器学习和人工智能的认证. 熟练掌握Python及其生态系统, 他在各种人工智能和机器学习技术方面拥有丰富的实践经验. Burcin目前的研究重点是大型语言模型(llm)的发展。, 专注于任务自动化以及在云环境中开发和部署人工智能产品, 特别是在谷歌云平台(GCP).

Portfolio

Onyx Relations Corp
人工智能(AI), Python,自然语言处理(NLP), GPT...
n11.com
谷歌云ML,谷歌云平台(GCP), GPT...
Onyx Relations Corp
人工智能(AI), GPT, Twitter API, Reddit API...

Experience

Availability

Full-time

Preferred Environment

Python 3, Jupyter Notebook, Natural Language Processing (NLP), GPT, 生成预训练变压器(GPT), Google Cloud Platform (GCP), Amazon Web Services (AWS), Visual Studio Code (VS Code), Ubuntu, Large Language Models (LLMs)

The most amazing...

...我建立了一个多功能机器人,使用llm实现自动化, 社交媒体上的情境感知互动, 可适应任何输入并部署在GCP上.

Work Experience

AI Developer (via Toptal)

2023 - 2024
Onyx Relations Corp
  • 开发了一个多功能机器人,能够发布特定主题和新闻稿,并在社交媒体平台上与用户互动, including Twitter and Reddit.
  • 整合和利用最先进的LLM/GPT技术, including OpenAI API and Gemini Pro, 为用户交互提供有机和上下文相关的响应.
  • 实现了检测和响应相关线程的功能, discussions, and trends across multiple platforms.
  • 增强了机器人对任何输入股票符号的适应性, 使用api从至少50个新闻源获取新闻数据, RSS feeds, and webpage parsing techniques.
  • 使用最新的法学硕士模型总结新闻数据,提供简洁、翔实的内容.
  • 使用各种技术将所有流程部署到Google云平台, such as Cloud Run, Cloud Functions, BigQuery, and Cloud Scheduler, 确保高效和可扩展的操作.
Technologies: 人工智能(AI), Python,自然语言处理(NLP), GPT, Large Language Models (LLMs), OpenAI, OpenAI GPT-4 API, Open-source LLMs, HTML Parsing, APIs, Google Cloud, Google Cloud Functions, Google BigQuery, Job Schedulers, Prompt Engineering, LangChain, NumPy, 检索增强生成(RAG), 生成预训练变压器3 (GPT-3), OpenAI GPT-3 API, Gemini, Anthropic, Claude, BERT, Generative AI, Llama 2, Yahoo! Finance

Senior Data Scientist

2022 - 2024
n11.com
  • 构建日常客户数据管道, weekly, 以及每月根据客户交易生成的功能. 使用Python在BigQuery中生成表的调度作业.
  • 重新设计并改进了流失模型,以检测流失并使用客户交易作为原始数据计算客户生命周期价值.
  • 根据使用平台活动日志和事务的客户行为对客户进行细分.
  • 使用客户交互数据开发和部署自定义聊天机器人. 在GCP中创建了自定义模型端点,在Cloud Run中创建了API,并为计划的模型再训练操作设计了Kubeflow管道.
  • 设计了一个HTML页面,使用办公室屏幕跟踪实时订单数量,并使用HTML动画来庆祝目标命中, CSS, 和JavaScript以及FastAPI在后端.
  • 作为团队的一员,在一个定制的内部推荐系统开发项目中工作,并为整个项目生命周期的设计做出贡献, including the API design.
  • 设计和开发欺诈和假冒产品检测方法, including image recognition, TF-IDF, 词法提取和文本嵌入生成, and keyword extraction.
Technologies: 谷歌云ML,谷歌云平台(GCP), GPT, Natural Language Processing (NLP), Python 3, Python, Google BigQuery, BigQuery, Apache Airflow, Cron, Cloud Dataflow, Machine Learning, Deep Learning, Unsupervised Learning, Customer Segmentation, Classification, Data Analysis, Data Science, Data Engineering, Data Pipelines, Natural Language Toolkit (NLTK), SpaCy, Artificial Intelligence (AI), Google Cloud Functions, Google Cloud, Kubeflow, APIs, Flask, Chatbots, HTML, CSS, JavaScript, OpenAI, ChatGPT, TensorFlow, Time Series, Beautiful Soup, Clustering, Supervised Machine Learning, Scikit-learn, Apache Beam, Large Language Models (LLMs), LangChain, NumPy, 生成预训练变压器3 (GPT-3), OpenAI GPT-3 API, BERT, Gemini API, OpenCV

AI Developer

2023 - 2023
Onyx Relations Corp
  • 开发了一个能够发布特定主题的机器人, press releases, 在社交媒体平台上与用户互动.
  • 集成和利用LLM/GPT技术,实现对用户交互的有机和上下文相关的响应.
  • 实现了检测和响应相关线程的功能, discussions, and trends across Twitter and Reddit.
  • 使用各种技术将所有流程部署到Google云平台, such as Cloud Run, Cloud Functions, BigQuery, and Cloud Scheduler, among others.
Technologies: 人工智能(AI), GPT, Twitter API, Reddit API, 生成预训练变压器(GPT), OpenAI, OpenAI GPT-4 API, Web Scraping, Natural Language Processing (NLP), Automation, Google Cloud Platform (GCP), Google Cloud Functions, Google Cloud, Docker, BigQuery, Machine Learning Operations (MLOps), ChatGPT, TensorFlow, Beautiful Soup, Scikit-learn, Large Language Models (LLMs), Prompt Engineering, LangChain, NumPy, 生成预训练变压器3 (GPT-3), OpenAI GPT-3 API, Generative AI, Llama 2, Yahoo! Finance

Data Scientist | AI Developer

2023 - 2023
Sole Entrepreneurship in US
  • 利用价格相关数据跟踪美国股市趋势策略,开发并进行回测.
  • 通过连接股票市场api,使用Python根据回测结果自动执行成功交易策略.
  • 在云端部署所有全自动交易机器人, 允许用户改变参数和开始/停止他们通过一个干净的前屏幕.
  • 创建单独的BigQuery表来记录每个交易机器人的关闭交易,并通过过滤选项将交易结果可视化,让用户使用Looker Studio分析机器人的性能.
Technologies: Trading, Artificial Intelligence (AI), Data Science, Data Analysis, Algorithmic Trading, Trend Analysis, Google Cloud, Google Cloud Platform (GCP), Google BigQuery, Looker, API Integration, Finance APIs, Finance, Time Series, Scikit-learn, NumPy, Yahoo! Finance

Senior Applied Scientist

2022 - 2022
Magnify
  • 在一个售后自动化和编排平台开发项目中担任ML模型开发人员. 基于Salesforce平台使用属性对客户进行细分.
  • Gathered, transformed, 并总结特征,定义了一种基于规则的客户流失算法,以检测客户之间可能的流失.
  • 从本机通过SSH连接到AWS VM实例, 在AWS的S3桶中建立ML Flow实验跟踪记录, 并使用Prefect生成实验跟踪报告.
Technologies: Python 3, Machine Learning Operations (MLOps), Clustering, Unsupervised Learning, Amazon SageMaker, Amazon Web Services (AWS), Artificial Intelligence (AI), Data Engineering, Python, Statistics, Data Science, Scikit-learn, Docker, Time Series, NumPy, PostgreSQL

Senior Data Scientist

2021 - 2022
Intertech (Emirates NBD Bank)
  • 开发NLP模型,使用索赔文档总结文本,对客户请求进行分类,并将其转发给相关部门.
  • 汇总员工的工作日志作为时间序列数据收集, 然后估计未来的工作计划未来的员工能力需求.
  • 建立异常检测模型,检测发票支付中的异常情况,并实施电子邮件警报系统,以便相关团队及时干预.
  • Constructed pipelines for gathering data from various sources such as relational databases and HTML or Excel files to generate reports; these were published via Power BI.
Technologies: Python 3, Microsoft SQL Server, Microsoft Power BI, Financial Modeling, Trend Forecasting, Natural Language Processing (NLP), GPT, 自然语言理解(NLU), Data Analysis, Microsoft Azure, Data Visualization, Artificial Intelligence (AI), Data Engineering, Python, ETL, SQL, Data Pipelines, Data Analytics, Data Science, Statistics, Natural Language Toolkit (NLTK), SpaCy, Time Series, Clustering, Supervised Machine Learning, Scikit-learn, NumPy

Senior Data Scientist

2020 - 2021
Sekerbank (Samruk - Kazyna Invest LLP)
  • 建立并提出零售贷款产品和贷款账户的倾向模型,以确定客户购买这些产品的倾向.
  • 开发并实现了基于资产对零售客户进行细分的聚类算法, liabilities, and product ownership.
  • 整理和分类客户对产品和服务的投诉文本,生成每周报告.
  • 开发基于客户产品所有权的购物篮分析项目,以改进营销活动.
  • 为日常客户数据的解析和分析构建管道, weekly, 每月执行报告,使报告准备工作自动化.
Technologies: Python 3, Oracle SQL, Predictive Modeling, Classification, Trend Forecasting, Machine Learning, Supervised Machine Learning, Machine Learning Operations (MLOps), Data Engineering, SQL, Python, Data Science, Data Analysis, Data Analytics, Data Pipelines, ETL, Scikit-learn, Pandas, Forecasting, Natural Language Toolkit (NLTK), Artificial Intelligence (AI), Time Series, Clustering, NumPy, PostgreSQL

Data Scientist

2019 - 2020
Vakifbank
  • 为零售和中小企业客户开发和部署产品倾向模型,以检测客户是否可能购买,并改进营销计划的客户定位.
  • 构建了基于客户余额账户的客户细分模型, transactions, credit cards, and loan usage behaviors.
  • 调查和更新当前使用的预测模型,以提高预测性能并简化结果.
  • 改进的报告生成管道,使基于客户数据的准备过程自动化.
Technologies: Python 3, Oracle SQL, Classification, Machine Learning Operations (MLOps), Clustering, Unsupervised Learning, Supervised Learning, Python, Statistics, Data Pipelines, Data Science, Data Analysis, Data Analytics, SQL, ETL, Machine Learning, Financial Modeling, Trading, Algorithmic Trading, Artificial Intelligence (AI), Finance, Finance APIs, Time Series, Supervised Machine Learning, Scikit-learn, NumPy

歌词生成器|一个网页抓取和歌词生成项目

http://github.com/burcins/LyricsGenerator
In this self-developed project, 我的目标是通过使用给定表演者的整个专辑的歌词来生成歌词. 我用鲍勃·迪伦(Bob Dylan)的歌词开发了我的模型,但它仍在接受新的考验.

In the first step, 我通过Beautiful Soup软件包解析了网页上的歌词,然后进行了清理,并为模型开发做好了准备. After that, 我创建了一个有几个层的双向LSTM模型,然后用一百次迭代来训练它. Eventually, 我为训练模型提供了最初的单词,它预测了额外的100个单词.

Twitter Sentiment Analysis

http://github.com/burcins/Twitter-Sentiment-Analysis
在这个项目中,我的目标是获得最新的Twitter tweet和干净的字符串. Afterward, 我会对每条推文逐一进行情绪分析,并为它们分配分数,以确定推文的积极或消极.

ATM Cash Demand Forecasting

http://github.com/burcins/Time-Series-Forecasting
该项目的主要目的是通过使用一年的每日存款和取款日志来预测下个月atm的每日现金需求.

该数据集包括三个特征:现金流入、现金流出和日期. It also contains 1,总共186个观测值,对应于1,186天,2016年1月1日至2019年3月31日. Eventually, 预计将分别预测2019年4月1日至2019年4月30日之间的现金流入和现金流出价值.

Term Deposit Propensity Prediction

http://github.com/burcins/Term-Deposit-Propensity-Prediction
项目的主要目标是建立一个端到端的机器学习项目,利用呼叫中心的数据来预测客户的定期存款购买倾向. 换句话说,我们试图预测客户购买定期存款的概率. In addition, 最后一部分用于客户聚类,以识别更有可能购买投资产品的客户.

该数据包含40,000条客户数据,具有14个特征,包括定期存款所有权.

Text Summarizer

http://huggingface.co/spaces/Burcin/ExtractiveSummarizer
在这个项目中,我的主要目标是根据文本的内容总结文本. 我开发了一个模型,并把它用一个界面部署到hug Face上. 这个界面允许用户总结维基百科的内容. 唯一的要求是从维基百科中获取主题及其收集的内容. 在摘要方面,该模型采用了两种不同的抽取摘要方法. 输出的句子数量取决于原始文本的长度.
2018 - 2020

商业分析硕士学位

雅典经济与商业大学-雅典,希腊

2011 - 2013

Master's Degree in Capital Markets

马尔马拉大学-伊斯坦布尔,土耳其

SEPTEMBER 2022 - PRESENT

MLOps Zoomcamp

DataTalks.Club

NOVEMBER 2020 - PRESENT

自然语言处理专业化

Coursera

Libraries/APIs

Pandas, Scikit-learn, Twitter API, NumPy, TensorFlow, Beautiful Soup, Natural Language Toolkit (NLTK), SpaCy, Reddit API, OpenCV

Tools

BigQuery, ChatGPT, PyCharm, Microsoft Power BI, Amazon SageMaker, Yahoo! 金融,Apache气流,Cron,云数据流,Grafana, Looker, Apache Beam

Languages

Python 3, Python, SQL, SAS, R, HTML, CSS, JavaScript

Paradigms

Data Science, ETL, Automation

Platforms

Jupyter Notebook, Google Cloud Platform (GCP), Docker, Kubeflow, Amazon Web Services (AWS), Visual Studio Code (VS Code), Ubuntu

Storage

Google Cloud, Microsoft SQL Server, Oracle SQL, MySQL, PostgreSQL, Data Pipelines, MongoDB, Cassandra, Redis, NoSQL

Frameworks

Flask, Streamlit

Other

Machine Learning, Natural Language Processing (NLP), Time Series, Classification, Clustering, Unsupervised Learning, Supervised Machine Learning, Data Analysis, Supervised Learning, Artificial Intelligence (AI), Data Analytics, Regression, Google BigQuery, Data Processing Automation, Google Cloud Functions, Finance, Ubuntu 20.04, Deep Learning, Statistics, Text Classification, Web Scraping, Machine Learning Operations (MLOps), Time Series Analysis, Financial Modeling, Trend Forecasting, Microsoft Azure, Data Visualization, Data Engineering, Trading, Algorithmic Trading, Financial Markets, Capital Markets, Stock Market, Stock Trading, Stock Exchange, Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNN), Long Short-term Memory (LSTM), Text Categorization, GPT, OpenAI, OpenAI GPT-4 API, Finance APIs, APIs, Chatbots, Large Language Models (LLMs), Prompt Engineering, LangChain, 生成预训练变压器3 (GPT-3), OpenAI GPT-3 API, Generative AI, Llama 2, Predictive Modeling, 自然语言理解(NLU), Forecasting, Stock Price Analysis, Stock Market Techinical Analysis, Financial Marketing, Big Data, Social Media Analytics, Sequence Models, Data Cleaning, Google Cloud ML, Customer Segmentation, MLflow, Prefect, Trend Analysis, API Integration, 生成预训练变压器(GPT), Open-source LLMs, HTML Parsing, Job Schedulers, 检索增强生成(RAG), Gemini, Anthropic, Claude, BERT, Gemini API

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