The Sewing Machine Reviews & OpinionsSubmit The Sewing Machine review or read customer reviews:
100 Reviews Found
I just inherited a treadle "red eye" made in New Jersey in 1913. It as my Great Grandmothers (bought second hand). It needs some oiling and tuning but as I work the treadle and smell the metal I feel it's history humming. Thank you for this book it is a true gift .
I know nothing about sewing, and this book is perfect. Almost ready to start the projects, which are simple but useful. I'm using this with my new Brother sewing machine
This was very insightful and well written with all the information to get someone started both was so worth buying, I've already started making some of the projects in the book with my daughter to get her into sewing.
I was picking up a sewing book hoping to learn how to patch up my torn jeans but got more than what I paid for. Kitty went over 50 different sewing patterns that beginners and experts can use. I especially like her design on coin purse and night gown sewing pattern. Do download her free book to get more sewing ideas
Sewing books for novices really should come with some instruction photos. This one includes none. Instructions are somewhat clear. Save your money and look for beginner projects on Pinterest instead - most have tons of photos plus video tutorials.
Should have read reviews before buying. Too bad can't give 0 stars. No pictures no patterns. Why the hell I need to know how to make travel toiletries holder. For real. Wtf.
This book is great for young readers and kids who love Blaze. My 5yr old absolutely loves Blaze and this is one of his favorite bed time books. He likes to read along with it and that encourages him to read more and more. It has good pictures and the basic story from the first Blaze and the Monster Machines, where Blaze meets his new friends. I highly recommend this to boys who either already love Blaze or who might like to get into this cartoon on Nick Jr. If you have a young boy, its worth buying!
My only real complaint about this book is that it doesn't read like the tv show. I have to add my own lines where Blaze and AJ are asking for help from the audience (my son) and I interject my own educational questions into the story so it's interactive like the show.
When I get a new or new-to-me cookbook the first thing I do is read it from cover to cover. Then I browse through it again and mark every recipe that I want to try. In this book I marked more than I didn't mark!
I have really been enjoying using these bread recipes. Some have ingredients that I never would have thought about using I think you will be proud to have this book in your cookbook collection and will refer to it often.
This is the first book about Machine Learning that I have read and it has been educational, really. I'm glad that I accepted it when it was gifted to me. One chapter that I learned a great deal from is the one on "The art of attracting people to your business through Machine Learning." With this, I can share ideas to the company that I am working for.
(I own the 1st edition, and was given early access to a pre-release PDF of the 2nd ed. My paperback copy just arrived.)This is the best book I've seen for professional software engineers to bootstrap themselves into Data Science, Machine Learning and (with the 2nd ed) Deep Learning. It makes heavy use of the scikit-learn library; and the latter chapters give an excellent high-level overview of TensorFlow. Books in this space can often feel either too basic or too academic. Not this one -- for me it hits the sweet spot of explaining and doing.What I love about Raschka's writing is how he builds up from theory to practical code. It lays out the concepts, math, and code together which helps comprehension. So, if you happen to be rusty in math, like me, you can look to the code to help explain what the equations actually do. The chapters of the book build up from each other; so many of the examples feel like they can be used as recipes for building your own custom models.
I've read through both Python Machine Learning -1st edition and 2nd edition (review version) and ran every codes provided in both is 2nd edition added further explanations and clarifications to the 1st addition, together with added chapters for two widely-used deep learning algorithms of CNN (for image processing) and RNN (for language translation) using is book is one of the few machine learning books currently available in the market that provide fully-integrated, fully-working Python implementation codes. The author successfully made tremendous efforts in bringing a variety of sophisticated machine learning algorithms in both classical statistical learning and deep learning by simple, straightforward and clear explanation together with fully-working step-by-step python codes down to average readers with basic technical understanding in machine learning is book could be a best fit to students and industry people who are interested in practical implementation and application of a variety of machine learning algorithms.
The second edition are fully revised and the error and typo in 1st edition are changed accordingly, the machine learning part are almost same but come up with new part for basic deep learning, I quickly looked through some deep learning chapters and enjoyed it, it's not complex and the author did nice job to explain it clearly.
This updated and expanded edition of python machine learning is a must have for every person involved with practical machine learning. The book not only presents a very well thought overview of a wide range of machine learning algorithms, but also shows the best practices when it comes to getting the most out of machine learning e clever choice of presenting applied case studies hand in hand with the corresponding ML math using python adds a lot of value to the book; this allows one to deep dive into pandas, matplotlib and sklearn. The last few chapters lay a strong foundation in neural networks model building and deep learning using google's tensorflow API.Full disclosure: I already own the 1st edition of this book and I received an early draft copy of the 2nd edition. I volunteered to review the last few chapters of the book.
A year ago, I gave a five-star rating to the book's first edition, picking it as my favorite among nine, mostly Packt-published, data-science/machine-learning-with-Python titles. The #1 subjective rank still stands, but there are two reasons why I want to reduce my rating of Version 2 to three stars, or "It's okay".First, there is a framing effect, or lack thereof. Whereas the first time, I had had the "warm up" of reading worse Packt books before I read Version 1 - and the book looked great compared to what came before it - this time I *start* from Version 2, and realize that it is a good Packt book, but a Packt book nonetheless, i.e. something half-baked, scratchpad'y and cond, I feel that the book's average level dipped with the addition of a co-author and a 200-page, 5-chapter block on artificial neural networks. (These 200 pages, using TensorFlow, replaced 70 pages of ANN coverage, relying on Theano, in Version 1. This is 95% of the book's change from the first edition: the non-ANN Chapters 1-11 grew slightly, by 20-plus pages. If ANNs - currently hyped as "deep learning" - are not your thing, you can save money and go with Version 1). I am new to TensorFlow, and I read pages 424-433 carefully. I did not enjoy it, and decided to order "Hands-on Machine Learning with Scikit-Learn and TensorFlow" by Geron, published by O' here we are, with "It's okay". My advice to budding data scientists would be: use this book, but only for code samples. Get a proper book, like "Introduction to statistical learning" by James et al. or "Elements of Statistical Learning" by Hastie and Tibshirani, to understand the methods.
This is such an informative book! It covers most machine learning algorithms divided by genre . From a teaching point of view, the book is quite comprehensive. The book is filled with beautiful graphs and other figures to further help the reader along in their understanding of machine learning. Indeed this book is well presented and I definitely recommend this book!
The book has done a good job in providing "Hands-On" material to go along with theoretical understanding of Machine Learning. The author, as an expert practitioner, provides code on to clean up data, find relevant attributes, and use different and alternate methods to understand data. This a great introduction to practical matters in Machine Learning. It is a great companion to be able to run experiments to practice the theory,
This is without a doubt the best resource I've come accross for machine and deep learning.I've taken online classes and read other books,but Gabriel's explanations are very clear and simple.Highly recommended.
Decided to buy it after 5 minutes of reading. One thing really amazed me: For a topic as complex as machine learning, it's usually really hard to be comprehended, especially for people like me with 0 technical background. However, the author tackled this beast, broke it down, and fed it to us on a neat and exquisite silver palate. Kudos for the author, great job!
Hands-down the best book on machine learning I have read to date (and I have three other books). Not only does the first half of the book give you a nice overview of the major ML techniques, but the second half illustrates how to implement many of these in Scikit-Learn. The author has a very clear style.
This was a great read for me. The book teach me everything about machine learning. I like the hand on exercise given, it is simple and easy to follow. I have not yet tried the other methods but I will surely practice it.
Really good for learning Scikit-Learn and just machine learning itself. Haven't gotten started on tensor flow yet but I am sure it will be great. highly recommended!
This is a great book for software engineers who want to know more about machine learning. I took the machine learning class on Coursera which was a great introduction in matlab to ML. I was looking for something with more details that covers all different algorithms. This book is exactly that. My python knowledge is also just basic and I haven't struggled at all.
I rarely leave product reviews, but this book is fantastic! Highly recommend it to anyone who wants to get started in ML. A week with this book did more than sorting through hundreds of free online tutorials for weeks.
Really good for learning Scikit Learn and just machine learning itself. Havent gotten started on tensorflow yet but I am sure it will be great!
1-0 to the Mean Machine. Mean Machine is an English reworking of Robert Aldrich's 1974 beefcake Burt Reynolds starrer, The Longest Yard. Substituting Gridiron for Soccer, director Barry Skolnick, along with his roll call of British "faces", is only aiming for one market. That of the footie worshipping clan that primarily resides within the United Kingdom. Very much a long way from competing on the same playing field as Aldrich's superior movie, Mean Machine does have enough about it to make it an enjoyable viewing outside of the excellently constructed soccer match that fills out the last third of the piece. But with the film's reputation being far from good, the chance that many others feel the same as me are pretty remote. About as remote as Accrington Stanley winning the English Premiere League one feels. The problem would seem to lay with the first hour, violence and humour thrust together does not always yield great rewards, and so it be with the wet behind the ears direction from Skolnick. Caught between a tough portrayal of British prison life and outright slapstick, it's an odd bedfellow that Skolnick can't quite get right. And with Guy Ritchie on the sidelines donning the "supervising producer" shirt, one can't help thinking that Ritchie would have made substantially more with the material to hand. But as "I" say, there's enough there for the discerning fan of blood and banter. Led by the watchable Jones, the cast, outside of the miscast David Hemmings as the Governor, pull out the stops to entertain the terrace faithful. Danny Dyer haters will enjoy him getting knocked about as he plays simpleton Billy Limpet, while Jason Statham is a joy as Monk, a Jock that even the Jocks are afraid of. While also putting in scene stealing shifts of note are Jamie Sives, Vas Blackwood and Omid Djalili. It's no piece of work to rank in the higher echelons of British movies - or sports movies in general for that matter. But in spite of its soggy formula and over reliance on the template film it's working from, it's very funny at times, and if you like soccer? Well the actual match is well worth the wait. 7/10 Footnote: The Longest Yard/Mean Machine was met with another re- imaging in 2005 with Adam Sandler as the disgraced lead protagonist. Proof positive that it's either a formula that many can't resist? Or that it's one that some feel still hasn't yet met its potential?
This is a low-budget 70's film which stems from the cinematic crazes of both the 'evilly-implemented mind control' ('The Manchurian Candidate' and 'The Ipcress File') and 'paranoia about government conspiracy' subgenres that were fervently expressed in the Vietnam/Watergate era of American cinema. For me, growing up watching James Best as Sheriff Rosco P. Coltrane in 'The Dukes of Hazzard', it was intriguing to watch him here, as a priest selected as one of 4 paid volunteers for an experiment supposedly run by the ECC, an environmental organization. It ends up that it's just a cover to test an experimental mind-control 'Brain Machine' that the U.S. government wants, in order to keep it's citizens in line, in the name of 'keeping social order'. Admittedly, when one of the directors says that the future is surveillance, I couldn't help but shudder at the parallels to society today, in this post-9/11 era. Unfortunately, the more time that passes, the closer these Orwellian cinematic views of civilization and its discontents come to mirroring the way life has become. No spoilers, but the machine forces the person to tell the truth. Growing up, I have learned that honesty is not always the best policy. In fact, life has to endure the 'little white lie' in order to have things run peacefully. While no cinematic masterwork, this film more than suffices as Exhibit A for evidence. Definitely worth a watch, especially if you can handle 1970's, TV-movie-style filmmaking.
I can see the light at the end of the proverbial tunnel, as I'm nearing the end of my infamous Mill Creek 50-film 'Nightmare Worlds' pack. This was a really strange viewing experience, and honestly made me wonder if my red wine had been spiked with some hallucinogen by some ne'er-do-well prankster. It had some intriguing ideas, a big one being that the USA and USSR are afraid that China is going to destroy the world, so at the last minute, just before a scheduled space flight to investigate Venus, NASA administrators replace three of the astronauts with female counterparts, and include a mysterious large suitcase. Though it says 1972, you can distinctly feel that it was made years earlier, before the game-changers of '2001: A Space Odyssey' and the manned space flight to the moon completely changed the way sci-fi films were made (unless you're the sad saps behind monstrosities such as 'Star Odyssey', that go on as if any relationship with the way things are in real life is an entirely accidental and unintended coincidence). Most of it was made in 1966, but funding ran out, and it shows. The filmmakers couldn't even afford the intended climax, and that shows--the film simply ends. But for all of that, this bizarre experiment of a forced Adam and Eve scenario in outer space, as a future for Earth, is decent--and it would be two generations later, when in Christopher Nolan's 'Interstellar', that this idea would be fully realized with human decency and artistic integrity.
Just like the Bluetooth headset. It's horrible. App crashes, uses too many resources, uses too much battery, has too many permissions. You dont need access to my photos and videos. Way too intrusive on privacy, and won't even connect to their server to register it. No thank you. Take your garbage headset, throw it in the trash, and buy one that works. I dont need a babysitter on my head.
This was one of the few flash card makers that could use mp3s (for studying birdcalls) spent hours making a set I could listen to on my computer thinking I could listen to it on my phone as well, I pay the 3 dollars for the app(too much for what you really get) and it won't play the audio files on my phone. Utterly disappointing.
The app itself is great. But a lot of the content, since written by other people, can have some really annoying errors. Either as simple as spelling error or that they put the term and definition is the wrong place. So half the cards are in the correct order and the other half is in the reverse. So you see the answer first before the question. I wish there was a way to edit the cards you download to fix these simple, yet annoying, problems.
This app is perfect. It's easy to make a new flash card set, edit that set, create and delete cards. Its easy to sync your card sets if you use the website versus the app, downloading and uploading. I use this for learning japanese and it has been such a great help. Highly recommended for ease of use!
Been my go to flashcard app for 9 years running, simple and effective more than other competitors for sticking true to the flashcard model and allowing you to repeat cards in your deck until you have learned everything. I can't learn without this feature which seems to be too complicated with Anki to set up, impossible with Quizlet, and difficult on other sites as well. HUGE database of flashcards too.