Hello There! 👋 I'm Onur Koç, a dedicated and hard-working person who believes in honesty and good working relation. I have four years of Python programming experience. I am also experienced in Machine learning, data analysis, statistics, and SQL programming. ✔ I am an experienced MSc Statistics, Data Scientist with over six years in the industry, specializing in : - Machine Learning (Scikit-learn, Keras, Neural Networks, Supervised and Unsupervised learning) - NLP (Text Analysis, Sentiment Analysis, Topic Models, gensim, spacy, textacy, parts of speech analysis) - Image Processing (Computer Vision) - Dashboards - Statistical Analysis - Medical Statistics ✔Over six years' experience in the Data Science and Statistics field within various industries focussing on providing value through problem-solving and statistical analysis. - Languages/Technologies: Python, R - Frameworks: TensorFlow, Keras, Pytorch ,Django, Flask. - Libraries: Natural Language Processing: NLTK, Scikit-Learn, GenSim, Spacy - OCR: Tesseract, Abbay, AWS Textract, Redhat - Machine Learning / Deep Learning: Keras, Pytorch, Tensorflow - Data manipulation: Pandas, SciPy, Numpy, dplyr, tidyr, lubridate, and others. - Data Visualization: Matplotlib, Plotly, ggplot2, seaborn - Deployment Platform: AWS, Google Cloud - Online Training Platform:- Amazon SageMaker, Amazon Rekognition, Roboflow, AUTOML Skills: - Data analysis, visualization - Data cleaning and transformation - Code performance improving - Machine learning models - API integration I am always looking for challenges and would love to take your project as a challenge and prove my technical abilities. Past Competitions: - JPX Tokyo Stock Exchange Prediction (Kaggle) - Mars Spectrometry: Detect Evidence for Past Habitability (drivendata) (rank 16) - Employee Turnover Prediction (datacamp) - Can you find a better way to segment your customers ? (datacamp) Some selected tools I worked with: ✅ Machine Learning Algorithms (PCA, K-means, Random Forest, XGboost, Logistic Regression, SVM and etc) ✅ Statistical Modelling (Hypothesis Testing, Mixture Mixed Models, General Additive Models, Ordinal Regression, EM, MCMC, ARIMA etc) ✅ Computational methods in biostatistics ✅ Data Visualizations (ggplot2, matplotlib) ✅ Dashboards with R Shiny ✅ Geospatial analysis ✅ Natural Language Processing (NLP - topics clustering, text generation, sentiment classification) and text analysis. ✅ Deep Learning (Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks) ✅ Deep Learning Frameworks (Tensorflow, Flux.jl) ❔ Why hire me? ✅ Hard work and honesty: - I am a dedicated and hard-working person who believes in honesty and good working relation. I always try not to mess with my job. ✅ Curiosity: - I continuously improve myself and my skills by learning new things, and also, I am ready to learn while working on projects. ✅ High-quality product: - I will consistently deliver a good quality product, I will not accept jobs, I am not 100% sure that I will provide a good quality product, and I will not take jobs that do not fit my skill set. My Experience 👨🏻‍💻:- 🤹 Classical Machine Learning Algorithms ( Knowledge-Based AI, Regression, SVM, Decision Trees, Apriori, Thompson Sampling, Kernel PCA, LDA e.t.c) 🤖 Computer Vision (Media Pipe, End-End Object Detection, Yolo, Faster/Fast-RCNNs, Semantic and Instance Segmentation, Neural Style Transfer, OCR, TextRect e.t.c) 📰 Natural Language Processing (GPT, T5, BERT, BERTSum, Doc Product, Transformers, Visual Attention, Summarization, Text Classification, Similarity, Ranking, NER, Deep Speech e.t.c) 🖼 Generative Adversarial Networks (Super Resolution, Image-to-Image Translation, Face Aging, Clothing Translation, and Generating new Human Poses e.t.c) 📊 Choosing the Best Machine Learning Models and Hyperparameters Optimization (Grid Search, K-Fold Cross Validation, Cumulative Accuracy Profile, Accuracy Paradox, CM) 🩺 Machine Learning for Healthcare and Medicine (Medical Information Retrieval, Semantic Segmentation, Disease Prediction, Data Augmentation, Class Imbalance Handling e.t.c.) 📝Machine Learning, Deep Learning, and Data Science Content Writing

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Aug 14, 2022