Linear regression, Random Forest, and KNN in Python

Interested in your [login to view URL] i am curently working on histopathological images to classify cancer in image slides(tissues cancer identification) .i have experince in Python, building Machine Learning models, Deep learning for computer vision and Natural language processing are some of my strong suites. Image processing, Object detection and localization, images segmentation are some of the projects i have worked on. In NLP text classification, sentiment analysis, text generation are some of the interesting work being carried out. For deep learning and NLP following are the tools i am most equipped with: 1. Keras 2. Tensorflow 3. Pytorch 4. Natural Language Tool Kit (NLTK) [login to view URL] Scraping When it comes to project following are the topics i have worked on 1. Convolutional Neural Networks for computer vision and NLP 2. Long Short Term Memory (LSTM's) 3. Transfer Learning (for feature extraction and fine tuning) 4. Linear, Logistic models, SVM, KNN, Random forest models for regression and classification I promise to provide you with great service which you deserve.

*** Machine Learning and Pandas , Data Analysis **** Thank you for your attention. I read the project description with interest. I strongly believe I am the proper candidate. I fit all the requirements you mentioned, including Python. I can help you kindly and full time. Let us discuss in more detail through chat. Thanks.

hello, i am an expert in machine learning and deep learning in both python and R. I have a vast expertise in implementing machine learning algorithms and have done many hands on projects with these algorithms. I can assure you best quality work.

HELLO! As an: - Bachelor of Applied Mathematics - Engineer in Statistics and Applied Economics - Microsoft Office Technician (Microsoft Graduate: MOS Diploma), - I have skills in programming language R, Python, I am able, available and ready to do this kind of work in the best conditions, ------------------------------------------------------------

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