Yashi K.

Experienced data scientist with over 4 years of experience in machine learning projects. Active participant on Kaggle, a google backed platform for data science competitions, rated within Top 1% data scientists globally. Have experienced in deep neural networks, convolution neural networks, recurrent neural networks, genetic algorithms, natural language processing, support vector machines, and generative adversarial networks. 𝐒 𝐊 𝐈 𝐋 𝐋 𝐒 ------------------------- 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 : - CNN, - DNN, - RNN/LSTM, - GAN, - Transformers, - Auto-Encoders, - HMM-GMM - SVM, - Boosting, - Random forest, 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 : - C, - C++, - Python, - R, - Matlab, - CUDA(Beginner). 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸/𝗟𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 : - Tensorflow, - Tensorflow lite, - Tensorflow js, - Keras, - Pytorch, - RASA, - Pandas, - Scikit-learn, - Open CV, - Tesseract OCR, - Kaldi, - OpenFace, - SpaCy, - NLTK, - Open Pose, - Others as well based on experience. 𝗧𝗼𝗼𝗹 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 : - Jupyter-notebook - Google Colab - Pycharm - R-Studio 𝗣𝗮𝘀𝘁 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘄𝗼𝗿𝗸 : - Generating karyotype from Chromosome micro slide image. - Identify boundaries of wound and measurement of wound - Extensive object detection, Detection of Sky, Window, Glass, Tree, building. - automated tool for detecting norms and stereotypes in popular culture. - Deep Learning with Image processing for the transformation of style from one image to another. - Mobile embedded object detection model with TF-lite. - Developed an algorithm to generate a 3D model of faces from a single 2D mobile selfie using Python, Convolutional Neural Networks, PyTorch, and CUDA. - Created an algorithm for image and video compression using similarity between images with the help of OpenCV. - Developed an algorithm for the classification of different sounds of drones using MFCC and LPCC features and then SVM and HMM-GMM classifiers. - Created a default loan predictor algorithm with 99.4% accuracy using Python and deep neural networks. - Created an optical character recognition for English language using Python and OpenCV,. - Extracted the Legos from the videos and the classify it into 52 different classes using the convolutional neural network using Python. - Worked on the CNN based binary text classification for the movie reviews to identify the positive and negative reviews with neural networks and Python. - Developed an algorithm for moving object detection, which can find a moving object in a vibrant environment using deep neural networks, OpenCV, and Python. - Many other projects I have worked on. Few of them are signed with NDA. I shall be glad to provide any information/clarification that you might need to make a better decision. If you like my work. Please Direct Message me OR invite me to your job. I will happy to connect and take your project to success. Thanks for taking the time to read through my profile. Looking forward to talking to you. Thanks