Demystifying

A step-by-step guide in understanding the concept of dependence and how to apply it to validate directed acyclic graphs in causal inferenceContinue reading on Towards Data Science » A step-by-step guide in understanding the concept of dependence and how to apply it to validate directed acyclic graphs in causal inferenceContinue reading on Towards Data Science » FOLLOW US ON GOOGLE NEWS Read original article here Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In…

Machine learning is a rapidly evolving field within the broader field of artificial intelligence (AI). It involves the development of algorithms and models that enable computers to learn from and make predictions or decisions based on data. Machine learning has become increasingly popular in recent years due to its wide range of applications and its ability to automate complex tasks. What Is Machine Learning? At its core, machine learning is about creating mathematical models and algorithms that can learn from data.…

Exploring PyMC’s Insights with SHAP Framework via an Engaging Toy ExampleSHAP values (SHapley Additive exPlanations) are a game-theory-based method used to increase the transparency and interpretability of machine learning models. However, this method, along with other machine learning explainability frameworks, has rarely been applied to Bayesian models, which provide a posterior distribution capturing uncertainty in parameter estimates instead of point estimates used by classical machine learning models.While Bayesian…

When I first planned to start this blog, I had in mind to talk about my personal views on generative language technology. However, after sending my first draft to friends, family, and colleagues, it soon became clear that some background information about generative text AI itself was needed first. So, my first challenge is to offer an introduction and simple explanation about generative text AI. This is for all the folks who are flabbergasted by the wonder of generative text AI and wonder how and where the magic happens.…

Image by authorHow to best use this important metric for monitoring ranking modelsRanking models underpin many aspects of modern digital life, from search results to music recommendations. Anyone who has built a recommendation system understands the many challenges that come from developing and evaluating ranking models to serve their customers.While these challenges start in data preparation and model training and continue through model development and model deployment, often what tends to give data scientists and…

A practical overviewImage by author. AI-generated using Dall-E-2The Transformer architecture has been essential for some of the biggest breakthroughs in deep learning in recent years. Especially in the field of Natural Language Processing (NLP), pre-trained autoencoding models (like BERT ) and autoregressive models (like GPT-3 ) have continuously managed to outperform the state-of-the-art and reach human-like levels of text generation. One of the most important innovations of the Transformer is the use of attention…

Special thanks to Dankrad Feist and Aditya Asgaonkar for reviewSharding is the future of Ethereum scalability, and it will be key to helping the ecosystem support many thousands of transactions per second and allowing large portions of the world to regularly use the platform at an affordable cost. However, it is also one of the more misunderstood concepts in the Ethereum ecosystem and in blockchain ecosystems more broadly. It refers to a very specific set of ideas with very specific properties, but it often gets conflated…

A straightforward approach to dealing with imbalanced datasetsRecently, I found myself in the familiar situation of working with a vastly unbalanced dataset, which was impacting the training of my CNN model on a computer vision task. Whilst there are various ways of approaching this, the findings of a study into handling class imbalance when training CNN models on different datasets concluded that, in almost all cases, the best strategy was oversampling the minority class(es); increasing the frequency that images from…

The default file format for any data science workflowHave you ever used pd.read_csv() in pandas? Well, that command could have run ~50x faster if you had used parquet instead of CSV.Photo by Mike Benna on UnsplashIn this post we will discuss apache parquet, an extremely efficient and well-supported file format. The post is geared towards data practitioners (ML, DE, DS) so we’ll be focusing on high-level concepts and using SQL to talk through core concepts, but links for further resources can be found throughout the post…

 A University of Chicago scientist is demystifying the dark art of electrolyte design.Creating the Building Blocks for Next-Generation BatteriesWith more than a trillion tons of carbon dioxide now circulating in the atmosphere, and global temperatures projected to rise anywhere from 2 degrees to 9.7 degrees <span class="glossaryLink" aria-describedby="tt" data-cmtooltip="<div class=glossaryItemTitle>Fahrenheit</div><div class=glossaryItemBody>The Fahrenheit scale is a…