Megan Eaves-Egenes's Nightfaring explores our connection with the night sky Here in the northern hemisphere, January always feels like the longest, drabbest month of the year, so how lucky we are to have a host of new science books to enliven our days. This month, we can explore everything from what the arts bring to our lives to the unsung hero that is friction. Or what we lose when we light up our skies? Daisy Fancourt's Art Cure investigates the impact of the arts, including dancing, on our minds and bodies What if playing the piano, dancing, visiting art galleries or even lying in the mud listening to Wolf Alice at Glastonbury was good for the body, mind and longevity? Or what if it could help us develop brain resilience against dementia? In theory, she's well-placed to make the case as a professor of psychobiology and epidemiology at University College London and director of the WHO's arts and health initiative.

This paper describes the creation, optimization, and assessment of a question-answering (QA) model for a personalized learning assistant that uses BERT transformers customized for the Arabic language. The model was particularly finetuned on science textbooks in Palestinian curriculum. Our approach uses BERT's brilliant capabilities to automatically produce correct answers to questions in the field of science education. The model's ability to understand and extract pertinent information is improved by finetuning it using 11th and 12th grade biology book in Palestinian curriculum. This increases the model's efficacy in producing enlightening responses. Exact match (EM) and F1 score metrics are used to assess the model's performance; the results show an EM score of 20% and an F1 score of 51%. These findings show that the model can comprehend and react to questions in the context of Palestinian science book. The results demonstrate the potential of BERT-based QA models to support learning and understanding Arabic students questions.

Computer scientist Mark Lee picks out his top science books on the subject of AI, machine learning and intelligent algorithms. Artificial intelligence (AI) is the process of teaching a computer to carry out tasks that typically only a human brain could do, but there is much more to it that trying to crunch numbers on a computer. Artificial intelligence is everywhere, from the robots manufacturing cars in factories to the smartphone in your pocket, and understanding what AI actually is will give you a better understanding of the technology that surrounds us. Professor Mark Lee is a computer scientist at Aberystwyth University. His new book, How to Grow a Robot, is all about how to design robots and artificial intelligence so that they are more social, more friendly, more playful – more human.

With exponential growth over the past years, the data science field has become very popular in the IT sector. Many businesses have started adopting data science techniques in order to derive meaningful information to make precise business decisions. Because of this data science has become an in-demand skill and one of the most highly paid careers in the tech industry. In order to be a successful business data scientist, it is crucial to understand and know how to use complex algorithms to build models, manipulate different datasets found from various sources, and be able to analyze and present findings to non-technical audiences. With so many resources available one can use them to learn more about data science but nothing beats reading data science books.

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Dear friends, Welcome to the July 4th issue of the Sunday Briefing. This week we're happy to announce the second post of "Visualization for Science" substack: Time Series State Map so check it out and don't forget to Subscribe to V4Sci so you never miss a post! You can also checkout the latest post at G4Sci: Network Motifs: Frequent patterns in Graphs where we introduce the ESU algorithm for exhaustive enumeration of all subgraphs of a given size. You should Subscribe to G4Sci to make sure you never miss a post! Over at Medium, Competing CoVID-19 Strains is the most recent post on the Epidemiology series and Mediation is the latest for the Causality series while we continue to work on the particularly long section 3.8 of the Primer.

Artificial Intelligence (AI) is the study of how computers can be made to act intelligently. For most of us lay book (and movie) nerds, we mostly experience AI through science fiction where humans create robots to think and feel like people, and those robots eventually turn against their creators and seek to destroy them. While fiction may make us feel like we are decades away from this AI reality, some of the best books on artificial intelligence will show AI is actually a staple in most of our everyday lives. It's there when we say "Hey Google (or Alexa or Siri)" or when the item we were searching for on Amazon starts to show up in our Facebook feed. As artificial intelligence becomes even more ingrained within our lives both at work and at home, it's important to understand the topic.

Artificial intelligence (AI) is the process of teaching a computer to carry out tasks that typically only a human brain could do, but there is much more to it that trying to crunch numbers on a computer. Artificial intelligence is everywhere, from the robots manufacturing cars in factories to the smartphone in your pocket, and understanding what AI actually is will give you a better understanding of the technology that surrounds us. Professor Mark Lee is a computer scientist at Aberystwyth University. His new book, How to Grow a Robot, is all about how to design robots and artificial intelligence so that they are more social, more friendly, more playful – more human. Whether you're a beginner or deep into all things AI, as an expert in artificial intelligence, Mark's pick of science books about machine learning and intelligent algorithms will have you thinking in ones and zeros in no time.

Statistical methods are used at each step in an applied machine learning project. This means it is important to have a strong grasp of the fundamentals of the key findings from statistics and a working knowledge of relevant statistical methods. Unfortunately, statistics is not covered in many computer science and software engineering degree programs. Even if it is, it may be taught in a bottom-up, theory-first manner, making it unclear which parts are relevant on a given project. In this post, you will discover some top introductory books to statistics that I recommend if you are looking to jump-start your understanding of applied statistics. I own copies of all of these books, but I don't recommend you buy and read them all.