Abstract: This research delves into the utilization of Artificial Neural Networks (ANNs) as a powerful tool for predicting the overall ratings of books by leveraging a diverse set of attributes. To achieve this, we employ a comprehensive dataset sourced from Goodreads, enabling us to thoroughly examine the intricate connections between the different attributes of books and the ratings they receive from readers. In our investigation, we meticulously scrutinize how attributes such as genre, author, page count, publication year, and reader (...) reviews influence a book's overall rating. Through rigorous analysis and experimentation, we construct an advanced ANN model tailored for predictive analysis in the realm of book ratings. The outcomes of our study reveal the remarkable potential of ANNs in this domain. The ANN model exhibits an impressive level of accuracy when it comes to forecasting book ratings, underlining the efficacy and promise of artificial neural networks in enhancing our understanding and prediction of book evaluations. This research opens up new avenues for leveraging machine learning techniques to gain deeper insights into the dynamics of book ratings and reader preferences. (shrink)

Abstract: The aim behind analyzing the Goodreads dataset is to get a fair idea about the relationships between the multiple attributes a book might have, such as: the aggregate rating of each book, the trend of the authors over the years and books with numerous languages. With over a hundred thousand ratings, there are books which just tend to become popular as each day seems to pass. We proposed an Artificial Neural Network (ANN) model for predicting the overall rating (...) of books. The prediction is based on these features (bookID, title, authors, isbn, language_code, isbn13, # num_pages, ratings_count, text_reviews_count), which were used as input variables and (average_rating) as output variable for our ANN model. Our model were created, trained, and validated using data set in JNN environment, which its title is “Goodreads-books”. Model evaluation showed that the ANN model is able to predict correctly 99.78% of the validation samples. (shrink)

Today's academia is obsessed about writing and speaking gobbledygook. At least most of the time. It has little time in sitting still and actually reading fiction, poetry and say, Wittgenstein. One pretends to say fancy things about these authors but one does not actually read books anymore. COVID 19 Lockdown prompted this author to answer queries from students and peers about a reading list. So prepare a wide ranging list he did which covers everything from the version of Mahabharata one (...) ought to read to novels on celibacy. But then he chose to publish at Prabuddha Bharata over all other platforms because the Ramakrishna Mission has the finances to keep this list alive 200 years hence. This was written during COVID 19 Lockdown in India at the end of April, 2020. Nirad C Chaudhuri insisted on making a good bibliography in his magnum opus. This author follows Nirad C Chaudhuri in quietly speaking about how Harold Bloom plagiarised the Late Professor John Senior's reading list. The list also comments on Romanticism and the art of writing itself. The list on Hinduism is truly contrarian. One hopes that this list survives when GoodReads and other Listopias are no longer. -/- Today's academia is obsessed about writing and speaking gobbledygook. At least most of the time. It has little time in sitting still and actually reading fiction, poetry and say, Wittgenstein. One pretends to say fancy things about these authors but one does not actually read books anymore. COVID 19 Lockdown prompted this author to answer queries from students and peers about a reading list. So prepare a wide ranging list he did which covers everything from the version of Mahabharata one ought to read to novels on celibacy. But then he chose to publish at Prabuddha Bharata over all other platforms because the Ramakrishna Mission has the finances to keep this list alive 200 years hence. This was written during COVID 19 Lockdown in India at the end of April, 2020. Nirad C Chaudhuri insisted on making a good bibliography in his magnum opus. This author follows Nirad C Chaudhuri in quietly speaking about how Harold Bloom plagiarised the Late Professor John Senior's reading list. The list also comments on Romanticism and the art of writing itself. The list on Hinduism is truly contrarian. One hopes that this list survives when GoodReads and other Listopias are no longer. -/- These COVID 19 days, while the First world is mooning over syllabi for their kids and third and fourth world folks like me are tackling Umphan; I chose to prepare a new kind of syllabus. A syllabus which is not merely a list. In these days of incessant and meaningless webinars which my students can only spread memes about and only the poor and doctors will actually travel to white nations which are killing their own; here's a list which ends with Hindu classics which are contrarian. Nirad C Chaudhuri, a much maligned man in India and a forgotten polyglot in white privileged academia said we must first prepare a bibliography. So, Figure it out. I used some of the Hindu resources on recognition mentioned here and tried to work on Stephen King; a privileged white tenure track person from Trumpland just snowballed me. Now, this list is syllabi and also just a list of a bunch of books to read during Lockdowns which will be more common in the future because COVID 19, as Dr Fauci tells us; is here to stay. Even if one COVID 19 person is there; then along with Ebola, my white privileged tenure track fiends; off you go to gagaland. We in India already know these diseases. Go figure it out. (shrink)

The aim behind analyzing the Goodreads dataset is to get a fair idea about the relationships between the multiple attributes a book might have, such as: the aggregate rating of each book, the trend of the authors over the years and books with numerous languages. With over a hundred thousand ratings, there are books which just tend to become popular as each day seems to pass. We proposed an Artificial Neural Network (ANN) model for predicting the overall rating of (...) books. The prediction is based on these features (bookID, title, authors, isbn, language_code, isbn13, # num_pages, ratings_count, text_reviews_count), which were used as input variables and (average_rating) as output variable for our ANN model. Our model were created, trained, and validated using data set in JNN environment, which its title is “Goodreads-books”. Model evaluation showed that the ANN model is able to predict correctly 99.78% of the validation samples. (shrink)

We live in a universe that can be seen and experienced from many different perspectives. We therefore need to look at the universe from many different angles. Everything and everyone is a form of the universe being expressed in a particular way. In other words, each one of us can say with absolute certainly “We are the Universe!” Since we are the universe, each one of us provides a valuable perspective that complements the contributions of everyone and everything else around (...) us.Each of us is the universe being expressed in a particular location in a specific way. We’re all part of the same moving and evolving cosmos, but the view of it is unique from each of our respective locations. This suggests that the universe is not only omnicentric, but that it is also multiperspectival – there are many different, and equally valid, viewpoints on this. Each one of us is a cosmic laboratory within which we can discover the secrets of the universe.We speak in various ways, we are each the universe having become aware of itself in our own unique way. The insights that the universe has many different perspectives and is both cosmic and personal has great transformative potential, and is worth reflecting on deeply. Goodreads - official Amazon - Official. (shrink)