Summary of “Want to learn statistics? These are the best books, and they’re free to download”

The stats most people learn in high school or college come from the time when computations were done with pen and paper.
People who have taken intro statistics courses might recognize terms like “Normal distribution,” “t-distribution,” and “Least squares regression.” We learn about them, in large part, because these were convenient things to calculate with the tools available in the early 20th century.
We shouldn’t be learning this stuff anymore-or, at least, it shouldn’t be the first thing we learn.
As a former data scientist, there is no question I get asked more than, “What is the best way to learn statistics?” I always give the same answer: Read An Introduction to Statistical Learning.
If you finish that and want more, read The Elements of Statistical Learning.
Statistical learning is meant to take the best ideas from machine learning and computer science, and explain how they can be used and interpreted through a statistician’s lens.
“While knowledge of those topics is very valuable, we believe that they are not required in order to develop a solid conceptual understanding of how statistical learning methods work, and how they should be applied,” says Daniela Witten, a coauthor of An Introduction to Statistical Learning.
The statistical learning tools are wonderful in themselves, but I’ve found they work best for people who are motivated by a personal or professional project.

The orginal article.

Summary of “The GANfather: The man who’s given machines the gift of imagination”

The goal of GANs is to give machines something akin to an imagination.
When future historians of technology look back, they’re likely to see GANs as a big step toward creating machines with a human-like consciousness.
Yann LeCun, Facebook’s chief AI scientist, has called GANs “The coolest idea in deep learning in the last 20 years.” Another AI luminary, Andrew Ng, the former chief scientist of China’s Baidu, says GANs represent “a significant and fundamental advance” that’s inspired a growing global community of researchers.
In one widely publicized example last year, researchers at Nvidia, a chip company heavily invested in AI, trained a GAN to generate pictures of imaginary celebrities by studying real ones.
Once it’s been trained on a lot of dog photos, a GAN can generate a convincing fake image of a dog that has, say, a different pattern of spots; but it can’t conceive of an entirely new animal.
Researchers at Yale University and Lawrence Berkeley National Laboratory have developed a GAN that, after training on existing simulation data, learns to generate pretty accurate predictions of how a particular particle will behave, and does it much faster.
Hany Farid, who studies digital forensics at Dartmouth College, is working on better ways to spot fake videos, such as detecting slight changes in the color of faces caused by inhaling and exhaling that GANs find hard to mimic precisely.
Researchers are already highlighting the risk of “Black box” attacks, in which GANs are used to figure out the machine-learning models with which plenty of security programs spot malware.

The orginal article.

Summary of “Why Self-Taught Artificial Intelligence Has Trouble With the Real World”

In 2016, Google DeepMind’s AlphaGo thrashed champion Lee Sedol at the ancient board game Go after poring over millions of positions from tens of thousands of human games.
The past year also saw otherworldly self-taught bots emerge in settings as diverse as no-limit poker and Dota 2, a hugely popular multiplayer online video game in which fantasy-themed heroes battle for control of an alien world.
One characteristic shared by many games, chess and Go included, is that players can see all the pieces on both sides at all times.
An even more daunting game involving imperfect information is StarCraft II, another multiplayer online video game with a vast following.
Before the release of AlphaGo and its progeny, the DeepMind team achieved its first big, headline-grabbing result in 2013, when they used reinforcement learning to make a bot that learned to play seven Atari 2600 games, three of them at an expert level.
Within the larger category of reinforcement learning, board games and multiplayer games allow for an even more specific approach.
In game after game, an algorithm in a self-play system faces an equally matched foe.
Since 2008, hundreds of thousands of human players have attempted Foldit, an online game where users are scored on the stability and feasibility of the protein structures they fold.

The orginal article.

Summary of “How to Become World-Class at Anything”

To be passionate about something, we need to have some level of competence or mastery.
I know, from long experience, that if I want to get good at anything, I have to decide, with a strong determination, to apply myself to developing a seed of mastery in it.
Rather than sitting around waiting to die so that we can be reincarnated as Asian children, we can proactively bootstrap the process of learning and mastery any time we want.
We can use the planning and abstract thinking faculties of our highly evolved neocortices to trick our less evolved parts, such as our important emotional system, into coming along with us on the path to mastery.
Practice for a minimum amount of time each daySetting a lower limit on the amount of time you will spend on mastering a given skill helps you to quickly bootstrap enough competence that it will become self-sustaining.
Your positive attitude towards that seed of mastery will nourish it and it will grow, blossom, and transform into full-blown, world-class mastery.
In the process, we are bootstrapping the pathway to mastery by acting “As if” we are already masters.
We engage with the process, at whatever level of mastery we have attained, as a master would.

The orginal article.

Summary of “Don’t Know What You Want? Improve These 7 Universal Skills”

What does success look like? What do you want from life? What career do you want?
We think it’s the worst thing in the world if you don’t know what you want to do in life.
One of the biggest thinking errors that I’ve made was that I thought I needed to know what I exactly wanted to do with my life.
The truth is that no one knows what they truly want.
So it’s not important to know exactly what you want to do with your life.
It’s not even realistic to boldly claim “I know what I want!”.
If you can’t decide what direction you want to go in life, that’s automatically your #1 goal in life – to figure out where you want to go.
Persuasion: Learn how to get what you want in an ethical way.

The orginal article.

Summary of “4 Habits of People Who Are Always Learning New Skills”

Working in online learning, I’ve found that every year around this time there’s a burst of sign-ups from workers seeking new skills.
Having worked in HR at a large banking corporation and in strategic HR consulting, I’ve seen the effects of learning and development on career mobility – and what leads people to let it fall by the wayside.
Over time, working with users as well as learning experts, I’ve found that four crucial habits can make a tremendous difference.
With so many learning options available these days, people are often tempted to simply go to Google, type in some general search terms, and start one of the first courses that pops up.
To ensure relevance, you need to focus on learning the latest emerging skills.
As you get a sense of the most important skills to learn, ask these experts whether they can recommend specific online courses with practical value.
Researchers have found that “The sense of isolation” for some online learners “May make the difference between a successful and an unsuccessful online learning environment.” They call for more synchronous experiences.
You can run into the same issue with online learning.

The orginal article.

Summary of “20 tough lessons everyone should learn in their 20s”

If you learn how to effectively command a room, think on your feet, articulate yourself exceptionally and present your ideas in a way which others can digest, understand and feel inspired by, you will be a force to be reckoned with.
Read, ask questions, consider other answers, debate topics, admit when you’re wrong and surround yourself with people who are equally passionate and curious, as they will help propel you forward.
Eat well, laugh often, sweat every day, get enough sleep, limit harmful habits, give yourself a day off when you need it and treat your body as the critical vessel that it is.
Give yourself an hour of screen-free time before bed.
Always remain open, remain confident and remain honest with yourself and your heart.
Forgive yourself, forgive others, understand when someone or something is introducing negative energy into your life and forgive that too, but let it go as you do.
Unburden yourself so you can remain open to alternative experiences as you move forward.
Write your to-do lists in the morning, schedule your time, stay on track to the big picture on a daily basis but grant yourself permission to take a few leaps of faith, risks or breaths where necessary.

The orginal article.

Summary of “If It’s Important, Learn It Repeatedly”

I’m sure the Germans or the Japanese have a word that means, precisely, “Life-changing ideas that do not change our lives because we only read about them once, agree enthusiastically, and then forget them before we act on them.”
How many times has your mind been set ablaze by a profound truth from a book, podcast, article, or a speech, only for the idea to fade before you could do anything with it? How many millions of people read Steven Covey’s 7 Habits of Highly Effective People eight or ten or twenty-five years ago, agreed with it wholeheartedly, and never became highly effective in any of those ways?
Alain de Botton, in another wonderful book I read and immediately forgot, identified the problem, or at least a major part of it: when we only learn something once, we don’t really learn it-at least not well enough for it to change us much.
As an orthodox Jew, 300 days a year were marked out for commemoration and ritual repetition of ideas in the Torah, while as a Zen priest, one would be inducted to sit cross-legged and meditate up to twelve times between daybreak and nightfall.
Bringing a truth to mind repeatedly gives it an enduring, three-dimensional existence in your head, by reaching you in every mood and every context, in every season, both at times when you’re enthusiastic about it, and when you’re tired of hearing it.
If you’ve ever read a book a second time, you may have noticed that it’s an entirely different experience from the first time.
So in my case it warrants a second read, and a third read, perhaps many more, as I implement its increasingly familiar ideas.
The idea is to develop a modest but consistent meditation practice and a few mindful living habits, at a gentle pace of about ten minutes a day.

The orginal article.

Summary of “Funded by Gates and Zuckerberg, one company is on a quest to educate the world’s poorest kids”

“There are hundreds of millions of kids not in school and hundreds of millions in schools and not learning. Bridge exists to close that gap and to show its possible to run high-performing schools on a constricted budget,” says May. Not everyone is dazzled by Bridge’s approach or results, however.
Bridge says its classes are broken into fourths: one quarter of the time is spent activating prior knowledge; another quarter is the instructor teaching the kids material; the next emphasizes kids practicing what they’ve learned; and the last bit is used for summary and homework.
Bridge declined to offer retention rates, saying turnover was low; the New York Times says high turnover in its early days led Bridge to institute two-year contracts to secure teachers’ commitment.
Kids can ask questions when they want to, Bridge officials say.
Some critics suggest that they can largely be explained by the fact that Bridge kids come from families who have money to pay for school.
Among their concerns? By virtue of fees, Bridge excludes the poorest and most marginalized students in many of the countries where it operates.
Tilson, the Bridge investor and board member, says the pushback against Bridge is part of a campaign by teachers’ unions to shut the company down, since it does not always use certified teachers.
Of the nearly 40 people I spoke to about Bridge, everyone who was not an employee or investor in Bridge said that the company had an inherently confrontational culture.

The orginal article.

Summary of “The Biggest Wastes Of Time We Regret When We Get Older”

When I look back, my biggest time regrets aren’t spending too much time on Twitter or mismanaging my daily tasks.
Not only did I look like an arse, I could’ve also saved a fair amount of time that day by simply asking my boss what he meant.
There are a handful of reasons we don’t ask for help, but it’s usually because we’re too proud or scared, and that’s a huge waste of time, because it keeps you from moving forward.
Like a lot of people, I made some common bad decisions that wasted both my time and the time of the person I was with.
At the same time, it’s hard to say all bad relationships are a total waste of time, because you learn a lot about yourself from them.
Dwelling on them wastes your time, diminishes your confidence, and keeps you from getting on with your life.
Regret is another big waste of time, so there’s no point in beating yourself up over these.
The sooner you learn from them the sooner you can free up your time and energy to live the life you want.

The orginal article.