Harpreet Sahota ๐Ÿฅ‘ Profile picture
Jan 3 โ€ข 13 tweets โ€ข 7 min read
๐Ÿคฏ Say goodbye to lifeless textbooks and hello to an exciting way to learn statistics! ๐Ÿ’ช

I have a masters degree in statistics, but these 11 books taught me more about how statistics in the real world than any course I've taken.

Have you read any of them?๐Ÿ‘‡๐Ÿฝ๐Ÿงต

#66DaysOfData
๐Ÿ“š๐Ÿง Who says learning statistics has to be boring?!

๐Ÿค“ The Manga Guide to Statistics makes it fun and easy to learn all the basic concepts, with entertaining examples and applications.

Get it here:nostarch.com/mg_statistics.โ€ฆ
Learn to calculate regression equations and perform hypothesis tests with The Manga Guide to Regression Analysis.

You also learn: simple, multiple, and logistic regression to predict iced tea orders and bakery revenues, and calculate confidence intervals and odds ratios.
๐Ÿง Introduces you to the tools of data analysis like graphs, charts, and tables, and exploring how to use samples to answer questions.

๐Ÿ’ก Plus, the author covers common data collection problems like selection bias and measurement error and how to deal with them effectively.
Naked statistics is a classic and bound to be on any and every list of statistics books.

It's a great read with a number of real world case studies.

IMO, not as good as The Art of Statistics.

Get a FREE pdf here: penguinrandomhouse.ca/books/404461/nโ€ฆ
๐Ÿ“ˆ๐Ÿ”ฎWhy are so many predictions wrong?

๐Ÿค”The Signal And The Noise breaks it down: sometimes we get overwhelmed by masses of data and forget to be cautious and diligent in finding the important signals.

Get a FREE pdf here: forecastwatch.com/wp-content/uplโ€ฆ
๐Ÿง๐Ÿ’กHow to Measure Anything teaches you how to make smart decisions using applied logic and behavioral economics.

๐Ÿคฏ Discover how misframing what needs to be measured and misperception of measurement elements can lead to mismeasurement and perceptions of the immeasurable.
You won't believe the history behind Bayes' rule: discoverd in 1740s by amateur mathematician to solving WWII codebreaking and now used in DNA decoding and Homeland Security.

๐Ÿ”๐Ÿ’ป The Theory That Would Not Die explores the controversy and obsessions surrounding this theorem. ๐Ÿ”ฅ
How Not To Be Wrong will help you make better decisions, navigate life effortlessly, and assess risks like a pro.

๐Ÿ’ช๐Ÿฝ Here are 3 key lessons to get you started:
1) Math is mostly common sense.
2) Probability โ‰  risk.
3) Scientific research findings can be wrong.

๐Ÿค“
๐Ÿค” "The Success Equation" helps untangle the intricate strands of skill and luck in our lives and offers concrete tips on how to use this knowledge to make better decisions.

๐Ÿ’ช๐Ÿฝ Don't miss out on this must-read for anyone looking to succeed in business and life.
๐ŸŽฒ "Thinking in Bets" shows you how to objectively evaluate your beliefs, work around biases, and learn from the past.

๐Ÿ’ช๐Ÿฝ Every decision is a bet, and this guide will help you navigate the quantifiable risks and come out on top.
๐Ÿ’ฅ๐Ÿค” Fooled by Randomness uncovers the role of chance in business and investing, and how it influences our actions, decisions, and risk-taking.

๐Ÿคฏ Get a fresh perspective on the role of uncertainty in our world. ๐ŸŒ€
Which of these have you read?

Which do you recommend?

1. Follow me @DataScienceHarp for more of these
2. RT the tweet below & share w/ your friends
3. For SQL follow: @nevrekaraishwa2
4. For Python and ML follow: @SanthoshKumarS_ @GiftOjeabulu_ @Sumanth_077 @Saboo_Shubham_

โ€ข โ€ข โ€ข

Missing some Tweet in this thread? You can try to force a refresh
ใ€€

Keep Current with Harpreet Sahota ๐Ÿฅ‘

Harpreet Sahota ๐Ÿฅ‘ Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @DataScienceHarp

Jan 4
You shouldn't evaluate the performance of a deep learning model solely on accuracy.

You're missing the whole picture if that's all you're looking at.

There are 3 other factors you should consider when evaluating the performance of your model ๐Ÿ‘‡๐Ÿฝ

#deeplearning #ai
Flops (floating point operations)

This measures of the amount of computation required to train and run a model.

More complex models often require more flops, which can make them more expensive to use.
Parameters

The number of parameters in a model can also impact its performance.

Models with more parameters may fit the training data better, but they may also be more prone to overfitting and may not generalize well to new data.
Read 6 tweets
Jan 2
You don't need a bootcamp to get started in machine learning.

All you need are the right resources, discipline, and time.

Here are 6 of my favourite FREE resources to get you started.
1/ edX's Machine Learning with Python: A Practical Introduction

This course will give you all the tools you need to get started with supervised and unsupervised learning.

Time commitment: 4 hours a week and you're done in 2 weeks.

edx.org/course/machineโ€ฆ
2/ Cognitive class' Machine Learning with Python

You'll learn about real-life examples of Machine learning and how it affects society in ways you may not have guessed!

Time commitment: 7 hours a week and you'll be done in 2 weeks

cognitiveclass.ai/courses/machinโ€ฆ
Read 8 tweets
Jan 2
The curse of dimensionality is a major roadblock for machine learning practitioners.

But most don't fully understand it.

Don't be left in the dark - join me in this thread as I clarify and demystify this concept ๐Ÿ‘‡๐Ÿฝ๐Ÿงต
The Curse of Dimensionality (let's just call it "The Curse") refers to problems that occur when you try to use statistical methods in high-dimensional space.
As the number of features (dimensionality) increases, the data becomes relatively more sparse, and often exponentially more samples are needed to make statistically significant predictions.
Read 7 tweets
Jan 1
If I had to learn data analysis with Python in 2023, here's how I would do it.

Get ready to transform your data analysis skills with these highly recommended resources.

#66DaysOfData ๐Ÿ‘‡๐Ÿฝ๐Ÿงต
1/ Cognitive Class: Data Analysis with Python

You'll learn how to prepare data for analysis, perform statistical analyses, create data visualizations, predict trends from data, and more!

Spend 30 minutes a day, everyday, and you'll be done in 3 weeks.

cognitiveclass.ai/courses/data-aโ€ฆ
2/ Udacity's A/B Testing Course

This course will cover the design and analysis of A/B tests.

Spend 1 hour a day, everyday, and you'll be done in 4 weeks.

udacity.com/course/ab-testโ€ฆ
Read 7 tweets
Dec 30, 2022
Feature selection is a crucial part of building a good machine learning model.

But most data scientists don't think before they select features.

The fact is: feature selection in machine learning is not always necessary.

Here are 5 situation when you don't need it ๐Ÿ‘‡๐Ÿฝ๐Ÿงต
1. You have a small dataset that doesn't have many features.

If the data you're using is small and doesn't have many features, you don't need to do feature selection.
2. The features are already carefully selected

If the features you're using have already been carefully chosen and are important for the task you are trying to do, you don't need to do feature selection.
Read 7 tweets
Dec 29, 2022
Machine learning and Python go hand in hand.

Ready to take the first step towards a rewarding career in machine learning?

These 4 resources will help you learn Python and get started ๐Ÿ‘‡๐Ÿฝ๐Ÿงต

#100DaysOfCode #66DaysOfData #DeepLearning
1/ Python Principles

I've never seen anything like this course.

This is a text based course with an interactive coding environment that will teach you all the basics of Python.

There's lots of challenges and exercises, too.

This should take 2 weeks.

pythonprinciples.com/lessons/
2/ CognitiveClass' Python for Data Science

Spend 1 hour a day and you'll be done in a week.

cognitiveclass.ai/courses/pythonโ€ฆ
Read 7 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us on Twitter!

:(