Techno Blender
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Data Sharing Challenges: Privacy and Security Concerns | by Louise de Leyritz | Feb, 2023

Navigating privacy and security when implementing data sharingPrivacy & security: the biggest challenges for data sharing — Image from CastorData sharing can bring many benefits to a company but also comes with its own set of problems. Two major issues that companies often struggle with are Privacy & Security. We will discuss these concepts in this third article of a series dedicated to data sharing.No one really likes to talk about these topics. I’ll be the first to admit that they’re not the most exciting things…

Generative Adversarial Networks, Explained and Demonstrated | by Uri Almog | Dec, 2022

How GANs work and how you can use them to synthesize dataFig. 1 — Synthetic images of a person, generated entirely by a GAN. Image source: https://thispersondoesnotexist.com/ . License: https://github.com/lucidrains/stylegan2-pytorch/blob/master/LICENSE (MIT)If you’re working in deep learning, you’ve probably heard of GANs, or Generative Adversarial Networks (Goodfellow et al, 2014). In this post we will explain what GANs are, and discuss some use cases with real examples. I am adding to this post a link to my GAN…

Paper Review: A Deep Dive into Imagen | by Jamie McGowan | Feb, 2023

A critical analysis of Google’s impressive new text-to-image generation toolPhoto by Amanda Dalbjörn on UnsplashText-to-image synthesis is a research direction within the field of multimodal learning which has been the subject of many recent advancements . This review will focus on the article, ‘Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding’ .Here the authors attempt to achieve state-of-the-art photorealism and provide insights into a deeper level of language understanding within…

Identifying Drivers of Spotify Song Popularity With Causal ML | by Aashish Nair | Feb, 2023

IntroductionWhat makes a song tick? It’s easy to justify your love for a song when the artist hits a high note or recites a thought-provoking verse. It’s also easy to like a song solely because it was performed by one of your favorite artists. However, that alone does not account for the current music landscape. In this saturated market, where countless tracks have similar voices, genres, and styles, some tracks just happen to outperform others.This begs the question: are there more hidden/latent audio factors that…

The dynamic lot-size model: A mixed-integer programming approach | by Bruno Scalia C. F. Leite | Feb, 2023

The classical inventory management optimization problem solved in Python using PyomoPhoto by CHUTTERSNAP on UnsplashLot sizing problems are production planning problems with setups between production lots. By reason of these setups, it is often too costly to produce a given product in every period (Suwondo & Yuliando, 2012). In contrast, fewer setups are associated with higher holding inventory costs. Therefore, to obtain optimal costs, one should balance these operational aspects.Throughout this article, the problem…

Why data scientists should adopt Machine Learning (ML) pipelines | by YUNNA WEI | Feb, 2023

OpinionMLOps in Practice — as a data scientist, are you handing over a notebook or an ML pipeline to your ML engineers or DevOps engineers for the ML model to be deployed in a production environment?BackgroundIn my previous articles :I talked about the importance of building ML pipelines. In today’s article, I will deep dive into the topic of ML pipelines and explain in detail:Why is it necessary and important to build ML pipelinesWhat are the key components of a ML pipelineWhy and how data scientists should adopt ML…

SHAP for Time Series Event Detection | by Nakul Upadhya | Feb, 2023

Photo by Luke Chesser on UnsplashUsing a modified KernelSHAP for time-series event detectionFeature importance is a widespread technique used to explain how machine learning models make their predictions. The technique assigns a score or weight to each feature, indicating how much that feature contributes to the prediction. The scores can be used to identify the most important features and to understand how the model is making its predictions. One frequently used version of this is Shapley values, a model-agnostic metric…

Simple tool to foster connection among employees | by Zolzaya Luvsandorj | Feb, 2023

Office hourBuilding a happy and connected team with the help of PythonOne positive thing COVID-19 facilitated was to push more companies adopt flexible working arrangements. This adoption meant more of us can continue working from home even when lockdowns are over. While this flexibility is awesome in so many ways, one potential downside is that you can’t bump into people like you would normally in office and have those casual spontaneous conversations which help build better rapport with colleagues and make you feel part…

Use Classes for Generating Signals | by Omar Alkousa | Feb, 2023

Classes == More Code ReadabilityDuring your work with signal data, you might end up programming multiple functions and methods that can implement the process you want to use on the signal data. However, at some point, it might be hard to keep tracking the quality of your methods applied to signals without prior knowledge of this data. Therefore, generating signal data with prior known parameters helps you better understand your program and method. Generating signals, especially sinusoidal signals, is very common in signal…

Google’s MusicLM: from text description to music | by Salvatore Raieli | Feb, 2023

A new model is generating impressive music from just text promptimage generated by the authors using OpenAI DALL-EGoogle has released a new model capable of generating music from a textual description. The result? impressive.Actually, the idea of applying generative AI to music is not a new concept. There have been several attempts in recent years, including Riffusion, Dance Diffusion, Microsoft’s Museformer, and OpenAI’s Jukebox. Google itself had previously released a model called AudioML. Why would this model be…