SKU: 24515509048

Girl, Stop Apologizing: A Shame-Free Plan for Embracing and Achieving Your Goals

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Girl, Stop Apologizing: A Shame-Free Plan for Embracing and Achieving Your Goals"Hollis's writing is beautifully blunt, and she humbly thanks her fans for her success. Her actionable ideas and captivating voice will encourage women to believe in themselves." Publisher's Weekly (starred review) "I believe we can change the world. But first, we've got to stop living in fear of being judged for who we are." Rachel Hollis has seen it too often: women not living into their full potential. They feel a tugging on their hearts for

"Hollis's writing is beautifully blunt, and she humbly thanks her fans for her success. Her actionable ideas and captivating voice will encourage women to believe in themselves." - Publisher's Weekly (starred review)

"I believe we can change the world. But first, we've got to stop living in fear of being judged for who we are."

Rachel Hollis has seen it too often: women not living into their full potential. They feel a tugging on their hearts for something more, but they're afraid of embarrassment, of falling short of perfection, of not being enough.

In Girl, Stop Apologizing, #1 New York Times bestselling author and founder of a multimillion-dollar media company, Rachel Hollis sounds a wake-up call. She knows that many women have been taught to define themselves in light of other people--whether as wife, mother, daughter, or employee--instead of learning how to own who they are and what they want. With a challenge to women everywhere to stop talking themselves out of their dreams, Hollis identifies the excuses to let go of, the behaviors to adopt, and the skills to acquire on the path to growth, confidence, and believing in yourself.



Binding Type: Hardcover
Publisher: HarperCollins Leadership
Published: 03/05/2019
ISBN: 9781400209606
Pages: 240
Weight: 0.75lbs
Size: 8.40h x 5.70w x 1.00d

Review Citations: Publishers Weekly 01/14/2019
Booklist 03/01/2019 pg. 4
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SKU: 24515509048

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4.1 ★★★★★
Based on 11 reviews
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Zay
Belleville, US
★★★★★ 5
Upside down (Great)
Format: Hardcover
Was extremely relatable and a blessing I gifted this book and want it back lol but I will be ordering again
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on October 23, 2024
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Rory Derrick
Lake Worth, US
★★★★★ 5
Good book
Format: Paperback
Still working through it but I have no complaints. I have a shelf of no starch books and have not been disappointed by any. Some, of course, are better than others but this is a good book.
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Reviewed in the United States on December 2, 2021
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Cory P.
Lowell, US
★★★★★ 5
Dive into Algorithms is more like eating a Parfait than trying understand algorithms!
Format: Paperback
Seriously though great writing and explanation along with great history lessons. Also highly recommend for anyone working in the data science field.
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Reviewed in the United States on August 3, 2021
F
Verified Purchase
Frank Gonzalez
Grantham, US
★★★★★ 3
Ok content, not great explanations (2.5 our of 5 stars)
Format: Paperback
I found the contents of this book to be simply ok: either too simple, or the more complicated algorithms and concepts would not be as carefully explained as they should have been. It is not a terrible book, but it feels as though the author did not go over many drafts/iterations of this work.
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Reviewed in the United States on April 7, 2024
I
Ira Laefsky
Belleville, US
★★★★★ 5
An Excellent Self-Discovery Approach to Learning Algorithms
Format: Paperback
I have an Ivy League Master's Degree in Computer Science although it was accomplished 35 years ago. Of course, I had to complete an ACM-type course in Algorithms and Data Structures on the undergraduate and graduate level and managed to by rote accomplish enough to satisfy these courses. But until seeing this great book I never had the feeling of gaining an understanding of the approach to learning and building algorithms and the extent to which it is an important component of all programs. By a journey of guided self-discovery the author shows, not only the necessity of algorithms and their canonical forms, but a path to understanding the construction of algorithms to accomplish common and not so common practical problems. These range from the simple to understand, e.g. implementing Russian Peasant Multiplication, to advanced and up to date topics like Machine Learning. The highest praise I can give this book is that as a journey of guided self-discovery it produces an understanding in the reader of the process of constructing and understanding these algorithms and their place in all programming.
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Reviewed in the United States on February 7, 2021

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