F ans of Chris Ferrie's ABCs of Economics , ABCs of Space , and Organic Chemistry for Babies will love this introduction to neural networks for babies and toddlers! Help your future genius become the smartest baby in the room! It only takes a small spark to ignite a child's mind. Neural Networks for Babies by Chris Ferrie is a colorfully simple introduction to the study of how machines and computing systems are created in a way that was inspired by the biological neural networks in animal and human brains. With scientific and mathematical information from an expert, this installment of the Baby University board book series is the perfect book for enlightening the next generation of geniuses. After all, it's never too early to become a scientist! If you're looking for programming for babies, coding for babies, or more Baby University board books to surprise your little one, look no further! Neural Networks for Babies offers fun early learning for your little scientist!
I am Chris Ferrie, father of four and happy husband. My day job is academic research where I follow my curiosity through the word of quantum physics. My passion for communicating science has led from the most esoteric topics of mathematical physics to more recently writing children’s books.
I generally do not have an issue with Chris Ferrie (and his publisher Sourcebooks) calling his and his coauthor Sarah Kaiser's 2019 board book Neural Networks for Babies (since albeit that the titles of the Baby University series are obviously meant not really for actual babies but more for toddlers, for young children from about two to four or five years of age, the gimmicky book headings do tend to be interest inducing and to make parents consider these board books for their young children, and not bad this, as it is certainly a positive to start with, to introduce STEM themes early). But yes and unfortunately, I must admit that I am personally finding it rather annoying and majorly frustrating that a number of the Baby University books I have read to date either start nicely simple and then have Chris Ferrie (and his respective coauthors) render them too complex or they are right from the onset too advanced for a general board book audience (and no, for me, an unusually gifted, genius level young child like for example television's Sheldon Cooper would kind of be an anomaly here and really should not count all that much), and that most definitely, Neural Networks for Babies in my humble opinion falls rather heavily and with a majorly resounding and echoing thump into the latter camp so to speak, being one of those Chris Ferrie Baby University board books that are in my humble opinion much too complicated and too advanced for very young children.
Furthermore, if truth be told, even I myself (as an older, university educated but not too science and technology savvy adult) have found Neural Networks for Babies rather majorly and unnecessarily complex (and equally kind of strangely fantastical for STEM thematics to have neurons be actually described as talking, as seemingly freely chatting amongst themselves), so that I personally am in no way either comfortable with nor would I equally even want to have to explain what neural networks are to young children either, and yes, this certainly means that I would not want to be using Neural Networks for Babies in a read-aloud scenario one-on-one or as a group. For Chris Ferrie and Sarah Kaiser's text for Neural Networks for Babies is not only (as already shown and pointed out) annoyingly confusinlyg verbally rendered, Ferrie's illustrations are (in my opinion) even more so, are visually giving me a headache and do only very strangely, problematically (in other words not all that well) mirror the accompanying words (and that in particular very visually inclined young children might really end up being majorly confused and befuddled with and by Neural Networks for Babies, and that therefore, for and to me, Neural Networks for Babies rates with only one star and is also thus not recommended except with huge and major reservations and caveats).
Not actually pitched towards babies, but pitched mostly to their parents. Actually, scratch that. Not even pitched to parents (since this is boring to read), but to parents' friends. This is a gag baby registry gift and a gag shelf-warmer and a gag photo prop and that's about it. And I say this as an Expert, as a person that has run `import PyTorch` in my day.
my babies are better off playing with keras blocks as legos. portrays neural network as magic, does not explain how neurons can talk to each other. in my years of machine learning, i have never seen a neuron talk. i am not sure about the book's factual accuracy.
Unfortunately we were gifted this book along with a book on Robotics by the same author. Obviously it is not possible or even worth explaining neural networks to babies. Not worth the trees destroyed to print the book.
Please save your money on this joke book and give something that the child will actually enjoy.
Cool idea but I still think that it should be more for toddlers than babies. I guess introducing the words is a good thing but even though it's a simplified concept, it's still too advanced for a true baby, in my opinion.
This is perhaps a little too tough for most of us. It requires far more information. The narrator has, obviously, lost some of her spunk as she has narrated this entire series, however, it does show here.
Too high level. Material is insufficient for baby to re-implement even basic algorithms (AlexNet, DQN, etc.). Authors would do better to use fewer abstractions and include more code snippets
I'm not a baby so maybe they would understand more than I did, but the pictures were helpful and I do understand a little more now. Super creative concept.