Machine Learning Engineer with over 2.5 years of experience in different domains like IoT Data, AutoML models and Natural Language Processing, Excellent reputation for working collaboratively with team and resolving problems.
                    At Izenda, we have worked on creating a AutoML model using hyperopt. This enables users to just
                    upload their datasets and best model will be selected automatically so that they can easily make
                    predictions using the BI tool.
                    
                    We are now working on providing Natural Language search capabilities, in which users can make
                    queries in plain English and required data can be fetched from there databases.
                
At Lithion Power, I mostly did data analysis on huge amount of data gathered by batteries and some interesting projects too including geographical data, and learned a lot about production level code and different technologies like AWS, Git, IoT etc.
 
                    A Python application that uses hands detection and movement to draw images from live camera stream.
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                    I've trained a LSTM network to work as a language model on lyrics of a specific singer and then tried to genrate new lyrics.
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                    I trained a AlexNet model of CNN to predict category of natural sounds using ESC-50 dataset, that consists of 5-Second long recordings of 50 diffrent classes. Soundwaves were converted into spectrograms using FFT. Image shows example spectrogram on which model was trained.