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- 1. Anshuman Singh Personal Website-rimijoker.github.io as4917@srmist.edu.in | 6387520131 github.com/rimijoker | linkedin.com/in/iamanshumansingh EDUCATION SRM INSTITUTE OF SCIENCE AND TECHNOLOGY (KTR) B.TECH (COMPUTER SCIENCE ENGINEERING) 2022 (expected) | Chennai, IND CGPA-8.6/10 ST. ANJANI'S PUBLIC SCHOOL CBSE CLASS XII 2017 | Lucknow, IND COURSEWORK UNDERGRADUATE Calculus and Linear Algebra Programming for Problem Solving Data Structures and Algorithms Object Oriented Design and Programming Management Principles for Engineers Entrepreneurial Skill Development MOOCS Deep Learning Specialization (5 Courses)(deeplearning.ai) Issuing Organization: Coursera TensorFlow in Practice Specialization (4 Courses) (deeplearning.ai) Issuing Organization: Coursera Machine Learning (Stanford University) Issuing Organization: Coursera SKILLS NATURAL LANGUAGE PROCESSING: • RNNs• LSTMs •GRUs•Bag of words •GLoVe Embeddings •Word2Vec • N-grams COMPUTER VISION: • GANs • RCNNs • YOLO • CNNs MACHINE LEARNING: • RandomForest • GradientBoosting • K-Means • kNN • SVM LIBRARIES: • Tensorflow • Keras • PyTorch • fastai • Sci-kit Learn • nltk• XGBoost • Numpy • Pandas • Matplotlib • Plotly • Selenium LANGUAGES: • Python • C++ PROJECTS COLORIZATION USING GANS AND U-NET(GITHUB) | GANS, U-NET, CNNS, FASTAI, PYTORCH •Implemented a U-Net to colorize black and white images into coloured images. •The U-Net was built with the fastai framework which runs on top of PyTroch. •The encoder part of the U-Net was ResNet-18 and for the decoder part the convolution layers and pooling layers were replace with transpose-convolution layers and un-pooling layers. •The loss function was changed to perceptual loss/feature loss. •The U-Net was per-trained as a regression task with input as grayscale images and target as coloured images. •Then the Discriminator was per-trained using the generated images from the U-Net and the original coloured images. •Then the U-Net was trained as a GAN. SHAKESPEARE-GENERATOR(GITHUB) | LSTM, TENSORFLOW, KERAS •Implemented a LSTM with with Keras using Tensorflow as backend to generate text like William Shakespeare. GENERATING HUMAN FACES WITH GANS(GITHUB) | GANS, CNNS, TENSORFLOW, KERAS •Implemented a GAN to generate new human faces using the LWF faces dataset in Keras using Tensorflow as backend. •Random Noise was fed into a CNN(Generator) which was trained against 13,000 images of human faces with the help of a Discriminator. MALARIA PREDICTION USING CELL IMAGES | TRANSFER LEARNING, CNNS, TENSORFLOW, KERAS •Implemented a CNN on NIH malaria dataset to classify cell images into Infected and Uninfected. •Dense-Net121 architecture with pre-trained image-net weights was used for the classification and an accuracy of 0.94 was achieved. CATS VS DOGS | CNNS, TENSORFLOW, KERAS •Implemented a CNN with with Keras using Tensorflow as backend to classify images of dogs and cats. EXPERIENCE NEXT TECH LAB | MACHINE LEARNING PRACTITIONER MEMEBER IN MCCARTHY LAB July 2019 - Present | Chennai, IND • India’s first multi-disciplinary undergraduate student-led research lab. • Actively involved in the field of Artificial Intelligence. • Helping students new to the field by providing a structured learning path. VOLUNTEER NSS | NATIONAL SERVICE SCHEME