sagy t.

– Intense 6 months long ML bootcamp. ML: Supervised and Unsupervised. Deep Learning: Deep Learning, CNN, RNN, etc.
– Hours of python coding, implementing ML algorithms for different challenges, sometimes from scratch using only numpy.
– Understanding the math and intuition behind ML algorithms and how to implement them correctly.

– Final project- measuring and analyzing minute power outputs of a Stirling Engine by experiments using an innovative method developed for the project, designing and printing complex 3D parts for lab setup. Producing Powertrain performance graphs.
– Publishing a paper with findings from the experiment, 3 papers were published out of ~120 final projects.
– Presenting the paper and work in IEAI annual conference.

– Kaggle: projects- predicting future stock prices using LSTM. https://www.kaggle.com/sagytal/predict-stock-metrics-using-lstm
– Stock-Spider: Python software scraping stock financials from web, DCF calculations and graphs. Helping maintain portfolios.
– Arduino: IR remote for stereo receiver. DC engine encoder showing rpm- live on screen. Door indicator- locked or open.
– Udemy courses: Python basics, Python data science and machine learning.

– Preprocess data from patient-therapist sessions.
– Extensive EDA of data alongside statistical methods.
– Building predictive models alongside domain experts using deep-learning models suited for time series data.
– Work in a team, collaborations and analytical discussions.

– Developing and manufacturing medical devices, from idea to implementation.
– Work alongside the R&D team, work with contractors and individual work as well.
– Work in clean room and manufacturing devices for procedures.

– A unique mega-project which includes dredging 21 Million tons of salt per annum- project budget- $800M.
– Work with legal documentation- agreements between ICL and the state dealing with issues of jurisdiction and environment.
– Work with contractors on site and abroad.