“Yoav was invited to give a Deep Learning workshop at our offices as extra curriculum for the employees. The workshop was very thorough, engaging, and super interesting. Yoav really demystified deep learning for us, transforming it to something we can all understand, explain, and even use in our everyday work. If you want to know more about deep learning, really understand what goes on under the hood, and stop being afraid of stuff like neural networks, model training, and TensorFlow, this is the workshop for you! Highly recommended!”Ofer Moshaioff, Senior Software Engineer, Houzz
“I attended Yoav's Deep4Devs workshop as part of our company's aim to add neural network-based algorithms to our machine learning arsenal. I found the workshop to be of very high-value for me, mainly due to Yoav's focus on understanding the inner workings of machine learning metrics in general, and specifically neural networks. The use of Jupyter notebooks with written explanations alongside the code samples kept the workshop practical, and ensured that I'll be able to revisit covered topics in the future. The workshop doesn't try to treat neural networks as black-boxes to be used off-the-shelf, but rather gives the participants intuition and knowledge on the trade-offs in neural network design and the background needed to tailor them to specific needs. Yoav's knowledge of the subject is very impressive and thorough and you'll be hard pressed to find subject-relevant questions which he won't be able to answer.”Uri Barenholz, PhD, Head of Applied Research, trellis.ag
“Yoav, the workshop was wonderful! It was full of examples and tools for applications, you presented the material with a lot of patience, and it was a pleasure to meet you. Thank you!”Einat Aviv, Head of Risk Data Science, BlueVine
Assistant Professor at Tel Aviv University; a decade of experience teaching scientific Python in Academia and Industry.
Software developers and engineers interested in a pratctial introduction to deep learning.
An introduction to data processing, analysis, and visualization with Python combined with a primer in deep learning with neural networks.
16-24 hours of interactive sessions.
Instruction with code. Built-in exercises and problems. Laptops open with source code throughout all sesssions. Homework assignments for deep recitation.
Coding in Python, inside interactive Jupyter notebooks, using Keras, a popular deep learning library.
Understanding the math behind neural networks using Python and its scientific stack.
Training and using neural networks using Python, TensorFlow, and Keras.
Experience in software development (not necessarily Python) and a basic understanding of statistics, linear algebra, and calculus (BSc in exact sciences or similar).
Install the Anaconda with Python 3 Distribution for free.
Do some preliminary reading (2-3 hours) and exercises (3-4 hours after each day) at home or the office.
I'm an assistant professor at Tel Aviv University. I was a postdoctoral fellow at Stanford University and earned my PhD in Mathematical & Computational Biology from Tel Aviv University. I've been teaching Python in Academia and Industry since 2011, including at Tel Aviv University, IDC Herzliya, Applied Materials, Intuit, and KLA.
I enjoy solving and communicating complex problems and ideas. I develop and deliver Python programming workshops focused on numerical, scientific, and statistical applications in Israel, California, and anywhere else I'm needed - and now also on Zoom.
For more details and offerings click here.