I've Read Over 100 Books on Python. Here are the Top 3
Summary
TLDRThe speaker discusses their experience with over 100 Python books and highlights the importance of picking the right resources as a beginner. They compare learning Python to learning a language, emphasizing gradual practice rather than overwhelming study. Three book recommendations are made: 'Python Crash Course' for hands-on learning, 'Python Programming' for foundational computer science knowledge, and options for specific interests like data analysis or algorithms. The speaker also stresses the value of interactive learning, suggesting Brilliant.org as a tool to enhance understanding through engaging courses.
Takeaways
- 📚 The speaker has read over 100 Python books over the years and wants to share their top three recommendations.
- ❌ The speaker emphasizes avoiding books that are too overwhelming for beginners, with too much vocabulary and grammar.
- 🧠 Learning Python is similar to learning a language: start with the basics and build upon them through practice and projects.
- 📖 The first recommended book is 'Python Crash Course,' which splits learning into two parts: foundational knowledge and project-based applications.
- 👾 In 'Python Crash Course,' the second part includes projects like building a game (Space Invaders), data visualizations, and web apps.
- 💻 The second book recommendation is 'Python Programming' by John Zelle, which introduces the basics of computer science and helps with algorithmic thinking.
- 📝 The speaker suggests approaching 'Python Programming' by doing exercises at the end of each chapter and revisiting sections when stuck.
- 💡 For deeper computer science understanding, the speaker recommends 'Classic Computer Science Problems in Python' and 'Algorithms Illuminated.'
- 📊 If the learner's focus is data analysis, 'Learning Scientific Programming with Python' or 'Python Tools for Scientists' are excellent broad options.
- 🐼 For those specifically interested in learning pandas, the best book is 'Effective Pandas,' which offers in-depth instruction on using the pandas library.
Q & A
Why does the speaker compare learning Python to learning English?
-The speaker compares learning Python to learning English to emphasize that just memorizing vocabulary and grammar isn’t sufficient. Instead, one should focus on practical application, practice, and progressively build up knowledge through projects and problem-solving, similar to how one learns to communicate in a new language.
What is the speaker’s first recommended book for learning Python?
-The speaker's first recommended book is *Python Crash Course*, which is praised for its clear structure. It teaches the basics of Python in the first part and provides project-based learning in the second part, allowing beginners to apply what they’ve learned through hands-on coding projects.
Why does the speaker discourage using certain books for Python beginners?
-The speaker discourages using certain books for beginners because they contain too much vocabulary and grammar, which can overwhelm and discourage new learners. Such books are more suited for intermediate or advanced users.
What type of projects are included in the *Python Crash Course*?
-The projects in *Python Crash Course* include building a Space Invaders game, creating data visualizations, working with APIs, and developing a web app using Django. These projects help beginners apply foundational Python concepts to real-world applications.
Why does the speaker recommend *Python Programming* by John Zelle as the second book?
-The speaker recommends *Python Programming* by John Zelle because it provides a thorough introduction to computer science principles, helping learners avoid bad programming habits and strengthening their problem-solving and algorithmic thinking skills.
What approach does the speaker suggest for working through John Zelle’s *Python Programming*?
-The speaker suggests attempting the exercises at the end of each chapter and referring back to the relevant sections of the chapter when stuck. This iterative learning process helps learners build a solid understanding of computer science concepts.
What books does the speaker recommend for those interested in computer science and algorithms?
-The speaker recommends *Classic Computer Science Problems in Python* and *Algorithms Illuminated* for those interested in computer science and algorithms. These books cover search algorithms, technical interview prep, and basic algorithm concepts.
Which books does the speaker recommend for those interested in data analysis with Python?
-For data analysis, the speaker recommends *Learning Scientific Programming with Python* and *Python Tools for Scientists* for broad coverage of scientific and data analysis tools. For learners focused specifically on the pandas library, the speaker suggests *Effective Pandas*.
What advice does the speaker give about borrowing books?
-The speaker advises borrowing books from a library first to get a feel for whether or not they are suitable for the learner’s needs, avoiding the need to purchase multiple books before confirming their usefulness.
What is the main benefit of interactive learning, according to the speaker?
-The speaker highlights that interactive learning can be up to six times more effective than traditional learning methods because it actively engages the learner in problem-solving and skill-building, rather than passively absorbing information.
Outlines
📚 Learning Python: The Right Way
The speaker shares their extensive experience with Python books, highlighting the importance of choosing the right material for learning. They emphasize that just like learning English, learning Python should be an iterative process of learning and practicing. The speaker warns against overwhelming beginners with too much information at once, like a dictionary. They recommend 'Python Crash Course' as a great starting point because it covers the basics and then progresses to practical projects, such as building a Space Invaders game, data visualization, working with APIs, and web app development using Django. The book also introduces Git and GitHub and offers advice on text editors and IDEs.
🔍 Diving Deeper into Python and Computer Science
The speaker discusses the importance of understanding computer science fundamentals when learning Python, regardless of one's specific interests. They recommend 'Python Programming: An Introduction to Computer Science' for its comprehensive introduction to computer science and its role in preventing bad coding habits. The speaker suggests working through exercises at the end of each chapter to solidify understanding. They also provide multiple recommendations for further learning, depending on the learner's interests. For those interested in computer science, they suggest 'Classic Computer Science Problems in Python' and 'Algorithms Illuminated'. For data analysis, they recommend 'Learning Scientific Programming with Python', 'Python Tools for Data Analysis', and 'Effective Pandas'. The speaker also mentions the value of interactive learning and promotes Brilliant.org for its engaging and structured learning approach.
Mindmap
Keywords
💡Python Crash Course
💡Vocabulary and Grammar
💡Interactive Learning
💡Algorithms
💡Computer Science Fundamentals
💡Data Analysis
💡Pandas
💡Practice
💡Projects
💡Algorithmic Thinking
Highlights
The speaker has read over 100 Python books over several years and shares their top three recommendations.
A dictionary is used as an analogy to explain that just learning Python vocabulary and grammar isn't enough to master it; practice is essential.
The speaker emphasizes that beginners should choose their first book carefully, as some books overwhelm with too much information.
Recommendation 1: 'Python Crash Course' teaches the basics quickly and transitions into practical projects, such as a Space Invaders game, data visualization, and web apps using Django.
Part 1 of 'Python Crash Course' teaches foundations, while part 2 focuses on building projects, making it an ideal beginner's book.
Recommendation 2: 'Python Programming' by John Zelle introduces the basics of computer science and helps develop problem-solving skills.
The speaker advises using 'Python Programming' by attempting the exercises and reading the sections that explain the questions.
The book also helps learners develop algorithmic thinking and avoid bad coding habits.
Recommendation 3: For those interested in computer science and algorithms, 'Classic Computer Science Problems in Python' is recommended.
An alternative to dive deeper into algorithms is 'Algorithms Illuminated', which uses pseudocode to explain various algorithms.
For data analysis, the speaker recommends 'Learning Scientific Programming with Python', which covers tools needed for data analysis and scientific programming.
'Python Tools for Scientists' is another recommended book for those interested in data analysis.
If the focus is solely on learning pandas, the speaker recommends 'Effective Pandas', which covers everything you need to know about working with pandas.
The speaker emphasizes the importance of choosing a book based on personal learning goals and suggests borrowing books from libraries first to see if they are suitable.
Interactive learning, such as that offered by Brilliant.org, can be up to six times more effective than traditional methods.
Transcripts
I've read over a hundred books on python
I mean not all at once and that would be
ridiculous but over the course of years
I've read at least a 100 books on Python
and I want to share my three favorites
with you so these are some of the books
that I've read I don't know you might
recognize a few of those but before I
share with you my three favorites
there's something else that I want to
tell you that I think is even more
important than the three books that I'm
about to recommend so here it
is oh uh I can't actually find the thing
I want to show you in order to
demonstrate this so I'm going to have to
go and get one just bear with me when I
do
[Music]
that do you want to see what's in the
bag let's have a
look
yes it's a dictionary but how is an
English dictionary relevant to learning
python well I'm coming to that so
imagine if you wanted to learn English
and I said what you need to do is get
yourself a nice big dictionary like this
one that has loads of vocab and there's
a section on grammar too I did not know
that do you know what the collective
noun for Apes is it's a shrewdness of
Apes learn all the vocab learn all the
grammar and then you'll know English
that would be terrible advice it's also
terrible advice for learning python
which is why you have to choose your
first book carefully instead you learn a
little bit of vocab a little bit of
grammar and then you practice you
practice speaking and writing and at
first your facility with the language is
nowhere near enough to be able to
communicate the complexity of your
thoughts so you learn a bit more vocab a
bit more grammar and it becomes an
iterative process until you can
communicate exactly what it is that you
want to say and eventually if you're
lucky your ability with language
develops to the point where it helps you
come up with original thoughts and ideas
and it's exactly the same when learning
py which is why as a beginner there are
certain books you should avoid so as
well as giving you three book
recommendations I want to show you how
to recognize what makes a good book for
a
beginner let's start by looking at a
book that's bad for beginners this book
isn't very good for beginners there's
too much vocab too much grammar it's
overwhelming and it's more likely to put
you off that's not to say that it's a
bad book it's just not well suited to
someone that's new to programming and
new to python what you want is something
that gives you enough of the basics the
vocab and the grammar to get you started
on projects as quickly as possible which
is why I like this book what I like
about python crash course is that it's
split into two parts Part One teaches
you the foundations it teaches them
thoroughly but it doesn't linger too
long on them and part two takes what
you've learned and uses it to create
projects part one is that thick that's
all the python you need to know in order
to be able to work on the projects so
you learn the foundations of python in a
few pages and then you start doing
interesting things in part two which is
where all the projects are and the first
project you do is a game and um it's
pretty good actually it's Space Invaders
so you'll be building something like
that you'll also build an interactive
data visualization learn how to work
with apis and build a web app using
Django it'll introduce you to git and
GitHub and give you advice on text
editors and idees so you spend a lot of
time learning how to apply what you've
learned in part one to building projects
which is the whole point of coding in
the first place this really is an
absolutely excellent book for beginners
and it's my first recommendation book
two becomes a little bit more difficult
because learner needs diverge I don't
know why you want to Learn Python maybe
you want to do data analysis maybe you
want to develop web apps and that would
influence the choice of the second book
but this second book I think would be
useful for
everyone whether you want to Learn
Python to do data analysis or whether
you want to do web apps or whether you
want to go into computer science you
should have an understanding of at least
the basics of computer sence because
that will be very useful to you when
you're trying to problem solve further
down the line and that's why I would
recommend this book Python Programming
by John zel gives a very thorough
introduction ction to the basics of
computer science it will help to ensure
that you don't develop any really bad
habits as you teach yourself to code in
Python and it will help you to
understand why things should be done in
a particular way and as you work through
it you'll develop your algorithmic
thinking and problem solving skills and
I think that's an essential step for
anyone that's teaching themselves and
the way I would approach this book
especially if you've already started
with python crash course is go to the
end of each chapter
and attempt the exercises and when you
get stuck go to the section in the
chapter that explains that question or
helps to explain that question go
through every chapter that way and you
will get an overview and a foundation of
computer science that I think will stand
you in very good stead this book
actually is a very old version it even
talks about python one in here somewhere
there's a much newer
Edition the choice for book is well it's
trickier still because it really will
now depend on where your interests lie
so what I'm going to do is I'm going to
recommend more than one book but I'm not
suggesting you get them all just choose
the book depending on what it is that
you want to use Python for so if you
want to carry on in the same vein as
this book with exploring computer
science a bit further I would suggest
this it's called classic computer
science problems in Python and it's the
sort of things that you might get in a
technical interview search algorithms
that kind of thing and if you're
interested in computer science I really
think you'll like this book there is
another one as well if you want to go
down the algorithm route and explore
those algorithms illuminated this is an
excellent introductory book on
algorithms it's not actually in Python
it uses pseudo code to explain the
algorithms maybe you want to use Python
for data analysis and if that's the case
then there really are lots of books to
choose from in fact the choice is so
great that it can be paralyzing but I'm
going to give you three options for this
that won't disappoint so the first two
that give a sort of broad overview of
data science or to use Python for data
analysis are these two learning
scientific programming with python now I
know this says that it's covering
scientific programming but actually what
is covered in here are all the tools
that you would need in order to be able
to use Python for data and analysis so
that's a really good sort of broad book
on the subject and then there's this one
python tools for scientists which is
quite similar really it covers all of
the tools that you would need uh for
science but also for doing data analysis
and uh I really like these two books
although they don't say data analysis or
data science in the title they're
actually very good for learning the
skills that you need to do that however
if it's just pandas that you want to
learn then the best book on pandas that
I have seen is this one effective pandas
this will teach you how to do pretty
much anything you can imagine in pandas
it is a superb pandas book in fact this
is the first edition I think there is
now a second edition so check that
before you get it but if it's pandas
that you want to learn and you're not
interested in learning the other aspects
of data analysis then you don't need to
think twice about it this is the book to
get oh yeah one last thing it's always a
good idea if you can borrow the book
from a library first so you can get a
feel for whether or not it's right for
you did you know that Interactive
Learning can be up to six times more
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