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Einträge mit dem Tag author_m.
The Subtle Art of Not Giving a F*ck
 224 Seiten

Plus: The audiobook has a great narrator. At the core, this book has a set of substantial ideas and truths.

Not for me: I became tired of the constant "fucks" very quickly. I feel like I have outgrown this youthful language (in a boring way, not in an "I'm too classy" way).

I think this book can be a great pointer to recalibrate the values in your life. Personally, I just didn't like the packaging.

↑ 2022
2021 ↓
& Rebuilding Reliable Data Pipelines Through Modern Tools
 97 Seiten

Kompakte Übersicht über das Thema "Data Engineering": Was bedeutet es, eine "Data Pipeline" aufzubauen, worauf muss man achten? Prinzipiell interessant, aber leider bleibt der Autor sehr unkonkret und nennt wenig echte Beispiele. Für Entwickler:innen ist es meiner Meinung nach zu abstrakt, für "Manager:innen" setzt es dann doch zu viel technisches Verständnis voraus. Ich verstehe die Zielgruppe nicht so richtig, ich selbst war zumindest nicht Teil davon. Naja, es war ein kostenloses ebook, dafür war es okay.

Fatherland
 424 Seiten

A political thriller set in an alternative post-war Berlin where the Nazis had won the war. This was Robert Harris‘ first novel after he had researched the stories of the forged Hitler Diaries in the 1980s. He clearly succeeded in mixing history and fiction – I for one was quite captivated by the story.

↑ 2021
2020 ↓
Mythos
 448 Seiten

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.

Selling Hitler
 400 Seiten

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.

How I Killed Pluto and Why It Had It Coming
 288 Seiten

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.

Germany
 416 Seiten

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: 1. 1618-1648: The Thirty Year's War 2. 1806-ish: Napoleon's victory over Prussia; most distinctly Napoleon's entering and occupation of Berlin 3. 1933-1945: The "Third Reich" and the Holocaust 4. 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.

Python for Data Analysis
 452 Seiten

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 (foo and bar and 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.