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A very funny green book that raises pressing current issues about waste and recycling. When Frank's classmates notice that his name in the register reads Frank N. Stein they insist that he build a monster. The boys make a creature out of rubbish but then a flash of lightning brings the monster alive. However, when they discover that all the monster wants to do is eat rubbish, they quickly realise how useful the monster will be. But try telling that to parents and police, the army and the adult world in general! A very funny green book, that raises pressing current issues of about waste and recycling.
The monster that Frank N. Stein and his friends made out of rubbish turns out to be very useful, as all he wants to do is eat rubbish! However, this doesn't please everyone...
The monster that Frank N. Stein and his friends made out of rubbish turns out to be very useful, as all he wants to do is eat rubbish! However, this doesn't please everyone. In England the dustmen worry about being out of a job; in Germany the Greens object to the indiscriminate way the monster devours stuff that can be recycled ; and in a very poor country when Steinasaurus eats a whole mountain of rubbish that many people live off - well he is very unpopular indeed. Then to top it all the monster falls in love. Another hilarious book of the adventures of the good natured monster as he realises the value of recycling, saving the planet and living a green life. "A garbage-eating Monster! Now why didn't we think of that?" Tim Smit, The Eden Project
Everyone apart from the rubbish collectors a re pleased that the monster is helping the rubbish problem - so Frank decides to take the monster on a working holiday. There he discovers that other people rely on rubbish too '
Wondering what video to rent tonight? This bestselling, fact-packed guide is the only sourcebook you and your family will ever need. Mick Martin and Marsha Porter steer you toward the winners and warn you about the losers. DVD & Video Guide 2004 covers it all-more films than any other guide, plus your favorite serials, B-Westerns, made-for-TV movies, and old television programs! Each entry, conveniently alphabetized for easy access, includes a summary, fresh commentary, the director, major cast members, the year of release, and the MPAA rating, plus a reliable Martin and Porter rating-from Five Stars to Turkey-so you'll never get caught with a clunker again!
What if...this morning, when you opened your newspaper, went online, turned on the TV, the headline startled your memories back to childhood fears: MARY SHELLEY'S FRANKENSTEIN CREATURE FOUND... ALIVE!What if Mary Shelley's, FRANKENSTEIN, was really a true story?BACK FROM THE DEAD: the true sequel to Frankenstein is an assemblage of psychological drama, horror, romance, and science-fiction. The story follows the account by Sergio Carerra, the scientist who revives the thought-to-be mythical creature from a two-hundred year arctic freeze and, with help from his psychologist wife, Sophia, brings him into the family of man. The fantastical story the creature tells is at odds with his gothic sojourns to the 1790's through dreams and reveries; they reveal a unique perspective on Shelley' original story, why he survived, and what happened to his mate. Present-day society takes to this formidable beast, so different than his movie counterpart, in a wholly modern way. And his feelings and reactions to his unwanted resurrection give him hope where none existed before. But now that he's back, there are others interested in him for reasons not so apparent, and they will do anything to get what they want. Finally, after 200 years, we are about to learn the truth
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.