Interesting retelling of the stories surrounding the female US code breakers of WW2. I learned some things about the war in the Pacific that I didn't know before. It was mostly straight-forward though: The stories of how (mostly) women were recruited to break ciphers for the army and the navy, some explanation on basic code breaking principles, embedded in the chronological development of the war and its effect on American society. I didn't like the audio version too much, to be honest. The narration was a little robotic and a bit slow for my taste. In retrospect, I think I would have preferred the paper version.
Highlighting the gender data gap: The absence of information and mechanisms required to make life fair for both genders.
Caroline Criado Perez shows how "male" is almost always the norm and "female" the exception - from the workplace over the size of smartphones to medical research.
The data she presents draws a sobering picture of inequality across all areas of life. A very important book.
A book about deep learning that really caters to my preferred learning style: It covers a lot of real-world applications (text analysis, sentiment analysis, vision, ...) and provides clear and practical code examples that invite you to try for yourself. Ultimately, trying it out and building something yourself is the way to really grasp the concepts, I think, and this book does a really good job at it.
While Francois Chollet does give some introduction in the beginning, it may be too little for the complete beginner. For anyone starting at a slightly-above beginner to intermediate level, I'd wholeheartedly recommend this book to learn Deep Learning with Python.
The first time I really leaned into Greek mythology. Stephen Fry does a great job at retelling the myths, providing humor and context so that the stories stick. It's still a lot, so I won't remember all of it. This may also be because I listened to the audiobooks so I couldn't earmark or highlight certain chapters or characters. Still, Stephen Fry reads it himself, so I would definitely recommend the audio version. He's definitely my favorite person to read any audiobook in the English language.
Wow, what a story.
I was only vaguely aware of the publishing scandal surrounding the "Hitler diaries" in 1983. The Hamburg-based magazine Stern had spent millions to fetch them through one of their journalists who in turn received them from a dealer that managed to acquire them from East Germany. Except: None of this was true and honest. The Stern management had committed to the deal behind their editors' back, the journalist kept half the money for himself (and spent lavishly on Hitler memorabilia) and the dealer in fact did not acquire the "diaries", but obediently forged them one by one as more money kept pouring in.
I couldn't stop reading. This story has everything and raises some interesting questions aside from the story itself: To what lengths do we go to deceive ourselves if we desire for something to be true? How easy do we calm our inquisitory and skeptic nature if an authority we trust has provided us with enough plausible explanations, even if they themselves have been deceived due to a series of mistakes and oversights?
Robert Harris wrote this book in 1986, briefly after the whole story had collapsed. I do not know what additional information has come to light in the 30+ years since, so this book may in fact be a little out of date. Also, I would have wished for a little transparency on how Harris was able to reconstruct the series of events, down to individual conversations. If the book has shown me one thing, it is to be skeptical of someone's narration of events, as long as the source isn't validated completely. What remains is a little uncertainty as to which assumptions Harris had to make to be able to tell it in such a cohesive and compelling manner. In any case, a book well worth reading if the story interests you.
The story of astrophysicist Mike Brown whose calling it is to observe the skies, trying to find new objects in our solar system. When he finds one particular object, the space community has come to grips with the fact that Pluto may actually not be a planet - and what exactly is a planet anyways?
Extremely entertaining, and sometimes shocking to learn about the politics of "who saw it first". I liked it a lot.
The subtitle of the book is "Memories of a Nation" and that describes it pretty well: From a non-German's perspective, MacGregor, who is the director of the British museum, describes German history in the format of many little episodes, each centered around one object, person, place or theme. He highlights how these things are good examples that explain the formation of a collective identity. They are tied together under one overarching thesis: This German identity has been defined by four great traumas:
- 1618-1648: The Thirty Year's War
- 1806-ish: Napoleon's victory over Prussia; most distinctly Napoleon's entering and occupation of Berlin
- 1933-1945: The "Third Reich" and the Holocaust
- 1949-1990: The division of Germany in East and West.
This is a history book. But it isn't a book about all of German history. MacGregor cherry-picks to tell the stories that best illustrate his main thesis. I think this is actually the strength of the book: Told as multiple stories, it doesn't feel like a dry list of events. Instead, it's compelling, interesting and even entertaining to read.
I've highlighted much for further reading and can recommend this book to anyone who is interested in German history and who wants to understand how German identity has been and is being formed.
A book about data analysis with Python using the popular Pandas library (de-facto standard for data wrangling), written by the creator of Pandas himself. Or as I like to call it: The Pandas Book.
First of, don't get me wrong: The 3-star rating doesn't mean this is not a good book. It just wasn't written in a style that I would have personally preferred.
Pros:
- Very extensive coverage of (almost) the complete Pandas API. I feel like I have seen (and tried) all major Pandas features now.
- Many code examples to see features in action.
- Excellent last chapter where the author goes through real-world data sets and shows how to explore and analyse data using Pandas features.
Cons:
- Large majority of examples using dummy data (
fooandbarand random numbers). While this shows the technical interface, it didn't help me grasp the application potential in many cases. - The structure made the book feel like official API documentation extended with a bit of prose. To be fair, the author made that clear in the preface, but the book had promised me a "hands-on guide (...) packed with practical case studies", and I only found that to be true in the last chapter.
What helped me was having a group of friends to discuss the book. We read one chapter a week and shared our notebooks of playing around with Pandas and our own data sets. While I personally prefer a slightly different style of coding books, studying this one has helped tremendously in becoming more familiar and confident in using Pandas for my data science projects.
James Clear describes how habits work in your brain (4 stages: cue, craving, response, reward) and how you can use that knowledge to build good habits and break bad ones.
The framework makes sense and it's clearly laid out in the book. His examples gave good context and made the text enjoyable and quick to read.
One thing I didn't like were the many pointers to the website and newsletter. There are even two chapters in the end which are "bonus chapters", meaning you can get them if you sign up for the newsletter. The recommended reading at the end is... a pointer to the newsletter. Would have preferred to have this book be a bit separate from online growth strategies.
In any case, the content was really good and I'm sure I'll make use of this. I've already started implementing some strategies in my life.
I just finished the Von Braun biography 2 weeks ago and stumbled on this book in a book store around the same time. It had just come out in mid September. This is a fictional account the V2 rocket during WW2, told from two perspectives. It's a good story and particularly interesting to read briefly after the Von Braun biography. Naturally, there are many overlaps when it comes to fact-dropping. I went for the audio book, which was a good choice. The narrator's voice is very pleasant.
I don't know how to categorize this books. It's not exactly a personal finance book, but kind of. It's not exactly a book about the foundations of behavioural finance, but kind of. I think the best way to describe it is that it's a collection of essay-form chapters loosely following a few central concepts:
- It's better to be reasonable in investing than it is to be perfectly rational
- Aim for a large margin of safety -- in investing but also in any life decisions
- Saving is worthwhile without having to save "for something"
- Accept that randomness is part of reality
- View "risk" as the normal fee to pay for achieving high returns and don't even attempt to escape it (= don't try to time the market)
I think Morgan Housel did a great job with this book. He didn't craft a whole new framework like many business book attempt to do. He didn't try to, and I think this was exactly right. This is a book that connects the dots, so to speak. It was short, to the point, and a breeze to read.
A remarkable biography about one of the most interesting characters of the twentieth century: Wernher von Braun. He infamously was the chief rocket engineer in the Third Reich, and after 1945 lived in the USA, eventually becoming one of the leading managers behind the US space program.
I learned a lot about the entrepreneurial rocket boom of the early 20th century, the development of the V-2 rocket, and the Saturn program. The book goes into a lot of detail, in some places maybe even too much so, but overall all of it seemed important to understand von Braun's life.
Something remains unresolved for me personally: Really understanding von Braun's role and responsibility in the crimes of the V-2 production and the treatment of KZ prisoners. There appears to be very little hard evidence to come to a clear judgement on these questions. I don't think this is a shortcoming of the biography. It's more the ambiguity of the character Wernher von Braun and his role and standing in the history of the world.
A meticulous biography. Highly recommended to anyone who's interested in the detailed history of early space exploration.
This book lays out a scientist's view of the world, ranging from the history of important scientific findings to research papers from just a few years ago.
Brian Cox (professor, educator, enthusiast) writes beautifully and tells compelling stories about the wonders of science. As I've learned in this book, he actually spent the years of his PhD in Hamburg, being no stranger to the Reeperbahn and other attractions. High five, Mr. Cox. ✋
This is neither a text book, nor one cohesive story, which is maybe something to criticise. However, I didn't mind at all and liked the book a lot.
As a reader, I felt encouraged to ask questions with the curiosity of a child's mind and to look for the answers through the eyes of science.
As a bonus, the text was set with pretty typography.
This was the book I needed to take me one step further: From just knowing "how to train a neural network" to a better understanding of "MLOps", including training workflows, aspects of scalable serving, and reproducibility.
The three authors are employed at Google and it shows in many chapters: The example of choice is always a Google Cloud AI offering or a Tensorflow code snippet. They do make an effort to also mention competitor products and open source alternatives. Because their insight from Google provided them with this wide range of best practices, I won't hold any of this against the book.
The book isn't without its flaws, though. This (recent) first edition has a number of distracting errors (such as misleading numbers in figures and weird code indentation), plus the greyscale print makes it hard to read many of the figures. That fact cost the book its fifth star. A 2nd edition will probably catch up once it irons out these issues.
I for one will keep this book on my shelf for future reference. It's a great collection of best practices to move a team and an organization ahead in terms of "AI readiness".