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Automatic code generator for training Reinforcement Learning policies
Generate custom template code to train you reinforcement learning policy using a simple web UI built with streamlit. It includes different environments and can be expanded to support multiple policies and frameworks with an high level of flexible hyperparameters customization. The generated code can be easily downloaded as .py file or Jupyter Notebook so to immediately start training your model or use it as a baseline… Read more Continue reading Automatic code generator for training Reinforcement Learning policies
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How Genify used a Transformer-based model to build a recommender system that outperforms industry benchmarks
The rapid ascension of AI, and more recently of deep learning, comported a succession of many breakthroughs in the field of computer science. These have had a profound impact on both the academic and the business world. In particular, modern deep learning techniques applied to the pre-existing concept of recommender systems has given birth to a new, superior class of neural recommender systems, which are… Read more Continue reading How Genify used a Transformer-based model to build a recommender system that outperforms industry benchmarks
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Genify’s experience testing Amazon Personalize: learnings and limitations
Challenges of machine learning Machine learning is a complex field that borrows elements from different areas such as computer science, algebra and statistics. Hence, it is not immediate, even for experts in the field, to build strong machine learning models to solve predefined task. Furthermore, those models should also be optimized with a time-consuming and repetitive hyper-parameters search in order to find the best set… Read more Continue reading Genify’s experience testing Amazon Personalize: learnings and limitations
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SeqGAN: text generation with generative models
In this post we propose to review recent history of research in the Natural Language Generation (NLG) tasks of the Natural Language Processing domain. Realistic human-like language generation has been a challenge for researches that has recently come into greater focus with the release of large neural models for NLP like the GPT and BERT models. In this post we propose to focus ourselves on… Read more Continue reading SeqGAN: text generation with generative models
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How I prepared an Elite Super Spartan Race
There’s nothing mediocre about this middle distance race. The Spartan Super offers the ideal blend between distance and speed. Offering racers a true athletic test. If you consider yourself a more seasoned athlete determined to push beyond excuses, you just might have the mettle for a Spartan Super. Serving up 25+ Spartan Obstacles and 10+km of rugged terrain, the Spartan Super spares no one. Developed… Read more Continue reading How I prepared an Elite Super Spartan Race
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Min-max in array
Given an array v of n numbers, where n=2k, k>0 be a natural number, find the minimum and maximum element in v. There are no assumptions regarding the orders of the elements of v. A basic iterative approach would require 2(n-1) comparisons (n-1 comparisons to find the minimum and n-1 comparisons to find the maximum). However, your program MUST perform at most 3/2n-1 comparisons. Difficulty:… Read more Continue reading Min-max in array
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K-th smallest element in unsorted array
Given an array v of distinct numbers, and a number k where k is smaller than the size of v, find the k-th smallest element in the array. A simple solution would be first sorting the array in growing order and than selecting the k-th element which can be done in θ(n logn). However, your program MUST run in θ(n) on average. Difficulty: Medium. Input There… Read more Continue reading K-th smallest element in unsorted array
