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Schedule Interview NowMy name is Enes B. and I have over 5 years of experience in the tech industry. I specialize in the following technologies: Python Scikit-Learn, SQL, TensorFlow, Natural Language Processing, Keras, etc.. I hold a degree in Bachelor's degree. Some of the notable projects I've worked on include: Enes Bol's ML Engineering Portfolio, Binary Classification, Garbage Management at Istanbul, Energy Production Forecast, House-Price-Prediction. I am based in Istanbul, Turkey. I've successfully completed 5 projects while developing at Softaims.
I'm committed to continuous learning, always striving to stay current with the latest industry trends and technical methodologies. My work is driven by a genuine passion for solving complex, real-world challenges through creative and highly effective solutions. Through close collaboration with cross-functional teams, I've consistently helped businesses optimize critical processes, significantly improve user experiences, and build robust, scalable systems designed to last.
My professional philosophy is truly holistic: the goal isn't just to execute a task, but to deeply understand the project's broader business context. I place a high priority on user-centered design, maintaining rigorous quality standards, and directly achieving business goals—ensuring the solutions I build are technically sound and perfectly aligned with the client's vision. This rigorous approach is a hallmark of the development standards at Softaims.
Ultimately, my focus is on delivering measurable impact. I aim to contribute to impactful projects that directly help organizations grow and thrive in today's highly competitive landscape. I look forward to continuing to drive success for clients as a key professional at Softaims.
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Basarsoft
Portfolio Overview Experienced ML Engineer specialising in enterprise RAG systems, LLMs, and time series forecasting. Built production systems including: multi-tenant RAG platform with custom pipelin
Trained 11 classification algorithms for a classification project. Since the classes were unevenly distributed, 12 different sampling algorithms were used. Oversampling methods performed better accord
Description The project aims to identify priority areas where new garbage facilities, garbage recycling plants or other garbage-related facilities should be built. Project Steps 1-Estimation of th
Predicted wind electric energy based on features like wind, temperature, etc.
The house price was estimated based on the user's choices. Xgboost was used for training the model and Streamlit was used for deployment. The model is trying to estimate the house prices related to u
Bachelor's degree in Electrical and Electronic Engineering
2018-01-01-2022-01-01