I’ve mentored about 165 projects during the last five years at the companies where I work. The people who built those project all got jobs (mostly). The more I talk to companies interviewing today, the more apparent it is: A portfolio project is decisive when making hiring judgments. Jeremy Howard recommends it. Andrew Ng recommends […]
HandySpark is a new Python package designed to improve PySpark user experience, especially when it comes to exploratory data analysis, including visualization capabilities.
Have you ever wondered the workflow behind getting such a pizza delivered to your home? I mean, the full workflow, from the sowing of tomato seeds to the bike rider buzzing at your door! It turns out, it is not so different from a Machine Learning workflow.
Photo by G. Crescoli on Unsplash Originally posted on Towards Data Science. Introduction If you are training a binary classifier, chances are you are using binary cross-entropy / log loss as your loss function. Have you ever thought about what exactly does it mean to use this loss function? The thing is, given the ease of […]
Photo by Jesper Aggergaard on Unsplash Originally posted on Towards Data Science. Introduction This is the second post of my series on hyper-parameters. In this post, I will show you the importance of properly initializing the weights of your deep neural network. We will start with a naive initialization scheme and work out its issues, like […]
Photo by Immo Wegmann on Unsplash Originally posted on Towards Data Science. Introduction In my previous post, I invited you to wonder what exactly is going on under the hood when you train a neural network. Then I investigated the role of activation functions, illustrating the effect they have on the feature space using plots and […]
Introduction This is the first of a series of posts aiming at presenting visually, in a clear and concise way, some of the fundamental moving parts of training a neural network: the hyper-parameters. Originally posted on Towards Data Science. Motivation Deep Learning is all about hyper-parameters! Maybe this is an exaggeration, but having a sound […]
I’m Jose; I run Data Science Retreat and AI Deep Dive, a 3-month school that takes pretty advanced machine learners and gets them to work together with mentors to produce a killer deep learning portfolio project. We want these projects to have social impact (example: a malaria microscope). I’ve been doing startups for 10 years. […]
This post should give you an insider view of how it feels to be in the market for a deep learning engineer job. I have interviewed thousands of people in machine learning in the last five years; for deep learning, only a few dozens in the last year; I’ve been paying attention to the market, who goes where, salaries etc. It’s enough for me to form an impression.
If you go and take a relaxed, well paid, 9–5 early in your career, you are getting paid to forgo the growth in your capabilities. Ok, that’s fine, many people take that deal. More so in Germany, the number one country in the risk aversion scale (well, it would be off the scale if there […]
Quick brain dump of reasons. Some may be obvious, but I’m just not sure how much people know about Berlin: – Cheap, very cheap, living costs compared to other capitals. Rents are rising steadily, better move sooner than later – Inexpensive restaurants, you can have a decent lunch for 5.5 EUR in any part of […]