Building AI to inform people's fashion choices
An AI system that proposes easy changes to a person’s outfit to make it more fashionable. Our Fashion++ system uses a deep image-generation neural network to recognize garments and offer suggestions on what to remove, add, or swap. It can also recommend ways to adjust a piece of clothing, such as tucking in a shirt or rolling up the sleeves...
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Data Science Articles & Videos
Teaching AI to plan using language in a new open-source strategy game
Facebook AI has developed a new method of teaching AI to plan effectively, using natural language to break down complex problems into high-level plans and lower-level actions. Our system innovates by using two AI models — one that gives instructions in natural language and one that interprets and executes them — and it takes advantage of the structure in natural language in order to address unfamiliar tasks and situations. We’ve tested our approach using a new real-time strategy game called MiniRTSv2, and found it outperforms AI systems that simply try to directly imitate human gameplay...
Streamlit launches open-source ML application development framework
Streamlit, a new ML startup from industry veterans who worked at GoogleX and Zoox, launched today with a $6 million seed investment and a flexible new open-source tool to make it easier for machine learning engineers to create custom applications to interact with the data in their models...
Visualizing a Neural Net Controlling an Interplanetary Spacecraft Trajectory
I made this visualization from a research paper I wrote, Neural Network Based Optimal Control: Resilience to Missed Thrust Events for Long Duration Transfers. It's made by simulating a Mars to Earth Trajectory and letting the neural network control the spacecrafts thrust and flight path angle. It's made using Matlab...
How to Evaluate the Logistic Loss and not NaN trying
A naive implementation of the logistic regression loss can results in numerical indeterminacy even for moderate values. This post takes a closer look into the source of these instabilities and discusses more robust Python implementations...
Hamiltonian Graph Networks with ODE Integrators
We introduce an approach for imposing physically informed inductive biases in learned simulation models. We combine graph networks with a differentiable ordinary differential equation integrator as a mechanism for predicting future states, and a Hamiltonian as an internal representation. We find that our approach outperforms baselines without these biases in terms of predictive accuracy, energy accuracy, and zero-shot generalization to time-step sizes and integrator orders not experienced during training...
How much Math & Stats do I need on my Data Science resume?
Do I need a strong math background to pursue a career as a data scientist? We see a lot of questions like this. Its hard when you're trying to break into the field to know exactly how much math & stats you need. And, part of the reason for that is that it really depends...
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Tranzact is a fast paced, entrepreneurial company offering a well-rounded suite of marketing solutions to help insurance companies stay ahead of the competition. The Senior Data Scientist will be solving the toughest problems at Tranzact by using data. More specifically, responsible for gathering data, conducting analysis, building predictive algorithms and communicating findings to drive profitable growth and performance across Tranzact. Must have a strong grasp on the data structure, business needs, and statistical and predictive modeling. Minimum 7 years of experience building predictive algorithms...
Training & Resources
Stabilizing Generative Adversarial Network Training: A Survey
The process of training GANs remains challenging, suffering from instability issues such as mode collapse and vanishing gradients. This survey summarizes the approaches and methods employed for the purpose of stabilizing GAN training procedure. We provide a brief explanation behind the workings of GANs and categorize employed stabilization techniques outlining each of the approaches. Finally, we discuss the advantages and disadvantages of each of the methods, offering a comparative summary of the literature on stabilizing GAN training procedure...
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