Learning disabilities expert Dr. Sheldon Horowitz explains the different types of learning disabilities and their impact on people with LD.

To read more about learning disabilities, please visit http://www.ncld.org/types-learning-disabilities

This lesson will help you learn about setting SMART goals for yourself in your English studies, and how it can help you learn English faster. Tell us what your SMART goals are for English in the comments!

To make progress in English, you need to think about your goals. In this lesson, you'll learn how to set SMART goals and how this can help you learn English more effectively.

See the full version of this lesson on our website: https://www.oxfordonlineenglish.com/smart-goals

Contents:
1. How to Set SMART Goals 2:18
2. Use SMART Goals to Improve Your English Speaking 5:18
3. Use SMART Goals to Improve Your English Pronunciation 8:27
4. Use SMART Goals to Improve Your English Grammar 10:58


This lesson will help you learn:
- About SMART goals (specific, measurable, attainable, relevant, time-bound)
- What SMART goals are and why it's important to set them.
- How to add effective time limits to your goals.
- Ways to make sure your goals are achievable.
- How to make goals like 'Improving English Pronunciation', and set them up so you can achieve them using SMART goals.
- Ways to set minor goals so you can better achieve your bigger goals.

You can find more free English lessons like this on our website: https://www.oxfordonlineenglish.com/.

After being forced to miss the entire 2019 playoffs due to an emergency appendectomy, OG Anunoby talked to Josh Lewenberg about the progress he has made to get back in game shape. Lewenberg also asked OG what he learned from Kawhi Leonard as a teammate and his experience attending Kobe Bryant's mini camp this summer.

40-60 Beats Per Minutes (BPM)

http://www.baroquemusic.org


1 JS Bach – Suite 3 BWV 1068: Air 0:00

2 Vivaldi – Guitar Concerto: Largo 3:31

3 JS Bach – Clavier Concerto BWV 1056: Largo 7:35

4 Albinoni – Oboe Concerto Opus 9/11: Largo 10:46

5 Handel – Water Music, Suite 1: Air 14:38

6 Vivaldi – Four Seasons, Winter: Adagio 16:47

7 Wassenaer – Concerto 4: Adagio-Allegro 19:20

8 JS Bach – 3-Clavier Concerto BWV 1064 flute/violin version: Andante 25:05

9 Wassenaer – Concerto 3: Andante 31:48

10 Handel – Oboe Concerto 2: Andante 35:40

11 Boyce – Concerto Grosso in b: 4th movement 38:13

12 Geminiani – Concerto 9: Largo 39:42

13 Albinoni – Sonata (Symphony) Op 2/5: Adagio 44:27

14 Alessandro Scarlatti – Concerto 4: Allegro 46:61

15 JS Bach – Sonata for Harpsichord & Violin BWV 18: mvt 3 49:21

16 Corelli – Concerto Grosso Op 6/12: 3rd movement 56:15

17 JS Bach – Clavier Concerto BWV 1058: Adagio 58:14

18 Handel – Oboe Concerto 1: Adagio 1:04:45

19 Corelli – Concerto Grosso Op 6/1: 3rd movement 1:06:40

20 Alessandro Scarlatti – Sinfonia 12: Adagio-Allegro 1:10:24


Theological Hall Baroque Library in Prague
Photo taken by Ernest Glez. Roda -- found at -- https://500px.com/abariltur

Yann LeCun is one of the fathers of deep learning, the recent revolution in AI that has captivated the world with the possibility of what machines can learn from data. He is a professor at New York University, a Vice President & Chief AI Scientist at Facebook, co-recipient of the Turing Award for his work on deep learning. He is probably best known as the founding father of convolutional neural networks, in particular their early application to optical character recognition. This conversation is part of the Artificial Intelligence podcast.

INFO:
Podcast website: https://lexfridman.com/ai
Full episodes playlist: http://bit.ly/2EcbaKf
Clips playlist: http://bit.ly/2JYkbfZ

EPISODE LINKS:
Yann's Facebook: https://www.facebook.com/yann.lecun
Yann's Twitter: https://twitter.com/ylecun
Yann's Website: http://yann.lecun.com

OUTLINE:
0:00 - Introduction
1:11 - HAL 9000 and Space Odyssey 2001
7:49 - The surprising thing about deep learning
10:40 - What is learning?
18:04 - Knowledge representation
20:55 - Causal inference
24:43 - Neural networks and AI in the 1990s
34:03 - AGI and reducing ideas to practice
44:48 - Unsupervised learning
51:34 - Active learning
56:34 - Learning from very few examples
1:00:26 - Elon musk: deep learning and autonomous driving
1:03:00 - Next milestone for human-level intelligence
1:08:53 - Her
1:14:26 - Question for an AGI system

CONNECT:
- Subscribe to this YouTube channel
- Twitter: https://twitter.com/lexfridman
- LinkedIn: https://www.linkedin.com/in/lexfridman
- Facebook: https://www.facebook.com/lexfridman
- Instagram: https://www.instagram.com/lexfridman
- Medium: https://medium.com/@lexfridman
- Support on Patreon: https://www.patreon.com/lexfridman

Get 3 months of Audible for the price of one. Sign up at http://audible.com/patrickwillems or text "patrickwillems" to 500 500

PATREON ► https://www.patreon.com/patrickhwillems

CAN’T GET ENOUGH OF KEANU ► https://bit.ly/2JahAhx

THE INFINITY PODCAST ► https://bit.ly/2TqZtuA

REDDIT ► https://bit.ly/2Uj44j0
__

TWITTER: https://twitter.com/patrickhwillems
FACEBOOK: https://www.facebook.com/patrickhwillems
INSTAGRAM: http://instagram.com/patrickhwillems

__

Camera operator - Alex Roberts
Research/animated titles - Emma Logsdon
Special thanks to Ellie Fetting

__

Music by Epidemic Sound
__

SEND US SOME MAIL:
Patrick Willems
P.O. Box 380333
Brooklyn, NY 11238

Learning with Passion and Enthusiasm releases dopamine, which means it works better and is more fun. Support our channel visit http://www.patreon.com/sprouts

Join us at www.patreon.com/sprouts

Sources:
Brain on Cocaine
https://archives.drugabuse.gov..../NIDA_Notes/NNVol13N

Dopamine and Learning
http://www.scilearn.com/blog/d....opamine-learning-bra

Learning Enthusiastically
http://www.gerald-huether.de/M....ediathek/english/Lea

Happiness in anticipation of something nice
http://www.dw.com/en/the-neuro....biology-of-christmas

Script:
Learning happens inside our brain when new information connects with existing memory. When we are excited or enthusiastic our brain happens to do that much better.

In a famous experiment American psychologist Hans Breiter put cocaine addicts into an MRI. The effect of the drug excited the addicts and the researcher saw a lot of activity in what’s called the Nucleus Accumbent. German scientists did the same experiment with young men and pictures of Porsche cars, which caused the same area to light up. When they did it with pictures of a Daihatsu.. it didn’t. What’s going on here?

As soon as we expect something nice to happen, the brain releases it's happiness chemicals dopamine and endorphin as well as other neurotransmitters. While dopamine and endorphin delight us, the other neurotransmitters send information from A to B. This connects new information from outside the brain with stored memories inside... and that’s learning.

Unfortunately this doesn’t mean that everything “fun” helps us learn. Shopping for example makes us happy, but as German Neuroscientists Manfred Spitzer measured, it only lasts 12 seconds. Then the dopamine level drops and we have to shop more to bring it back up.

This happens because the brain releases neurotransmitters in anticipation of something nice. But once we get it, the dopamine rush ends and the information exchange slows. Accumulating new things therefore doesn’t make us happy, nor does it help us to learn. Being excited about something for a longer time or being surprised does.

For example: When we are excited to plan a trip with our friends or when we have an unexpected and inspiring conversation with a stranger, our brain releases neurotransmitters in abundance and we start recording with all our senses in high definition. The synapses add existing footage from the long-term memory to make it a creative and memorable experience. It’s like we turn on a learn turbo.

Neuroscientist Prof. Dr. Hüther even argues that young children can learn multiple languages and so many other things, mainly because of their ability to be excited. And most are excited about everything until they get held back to follow their interest by the expectations of their parents or schools.

When learning a new language in a boring class at age 35 however, we have little left to be excited about and hence we learn next to nothing. Prof. Hüther believes any 75-year old Chinese man, who falls in love with a young 65-year old British lady, will speak English very fast.

If you are able to constantly learn new things in an exciting way, the chemicals released in your brain are likely to outlive the pleasures of drugs or shopping. It seems as if happiness and learning not only come from the same region in our brain, but they also promote one another.

What is your experience? Is learning a side product of enthusiasm? Or can we learn without passion or interest? Share your thoughts in the comment below!

Researchers in Michigan showed that project-based learning in high-poverty communities can produce statistically significant gains in social studies and informational reading—see how they did it in this video.

Learn more about the study and download the Project PLACE curriculum on Edutopia.org:

https://www.edutopia.org/artic....le/projects-have-bee

in this video having learner test object bits type model question with answer and each question having 4 options.

I created this video overview of PBL for the teachers at my school. We implemented a new program in the elementary school that uses this effective teaching approach.

Here are some video examples of PBL projects we have done so far:
https://www.youtube.com/playli....st?list=PLYyk4fLjIwR

Update #1:
I also want to mention that the Kindergarten Driving Question was changed during the year. Instead we came up with, "How will you, as an engineer, create a Rube Goldberg machine?" It remains motivating and interesting, and requires core knowledge, but also easier to understand and a little more open-ended.
Additionally the PBL 101 Workbook is not available anymore. However you can find more PBL workbooks on the BIE.org site. https://shop.bie.org/store-c2.aspx

Update #2:
We have discarded the Kindergarten unit that used the example driving question shown in the video. We felt that it had a weak PBL scenario as well as a weak connection between the subject areas involved. Instead here are some driving questions we introduced to our students this year.
- How can we help our school become environmentally-friendly? (Kinder)
- How will you create a nature-inspired tool that can be used during a family activity? (1st Grade)
- How can you, as IDEO Toy Lab inventors, create a toy for kindergarten students? (2nd Grade)
- How can you develop a city plan that will improve the local community? (2nd Grade)
- How can we as architects, design a schoolhouse for a specific region? (3rd Grade)
- How can you as engineers design and create an “Apple” recording device for ELLs? (4th Grade)
- How will you prepare yourself to become a NASA Martian? (5th Grade)
- How will your team of game designers create a Breakout EDU game specifically for younger students? (5th Grade)
- How will you as environmental engineers, design, build and market a product that helps the environment? (5th Grade)

You can find videos that describe these PBL projects here:
https://www.youtube.com/playli....st?list=PLYyk4fLjIwR

OK GO’s music video: https://goo.gl/qwCSK
Buck Institute for Education website: www.bie.org
Flowchart of a PBL Project: https://goo.gl/tT4iGX
Essential Elements of PBL: http://bie.org/about/what_pbl
Essential Elements of PBL Checklist: http://goo.gl/9gLbcU

Help us caption and translate this video on Amara.org: http://www.amara.org/en/v/iKI/

Students with learning disabilities are twice as likely as their peers to drop out of high school, according to the National Center for Learning Disabilities. Betty Ann Bowser visited an elementary school that practices early intervention -- engaging students with technology and art to improve their chances of earning a diploma.

MIT 6.034 Artificial Intelligence, Fall 2010
View the complete course: http://ocw.mit.edu/6-034F10
Instructor: Patrick Winston

Can multiple weak classifiers be used to make a strong one? We examine the boosting algorithm, which adjusts the weight of each classifier, and work through the math. We end with how boosting doesn't seem to overfit, and mention some applications.

License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu

Kristin is a school principal who is passionate about working with teachers to help students learn in a way that sticks through spiralling curriculum. Through her funny and engaging talk, she shares the power of recursive teaching in math with some phenomenal results for student learning through changing teacher practice.

Kristin Phillips has a passion for educational change. She works closely with teachers and administrators at the school and board level to bring about pedagogical change based on current research and practices.

Her current interest is "recursive teaching" in order to better engage students and promote learning that "sticks". She is currently a principal at a grade 7-8 school in Kitchener, ON.

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx

Group 4 ID Model Presentation

Jeremy Howard is the founder of fast.ai, a research institute dedicated to make deep learning more accessible. He is also a Distinguished Research Scientist at the University of San Francisco, a former president of Kaggle as well a top-ranking competitor there, and in general, he's a successful entrepreneur, educator, research, and an inspiring personality in the AI community. This conversation is part of the Artificial Intelligence podcast.

INFO:
Podcast website: https://lexfridman.com/ai
Full episodes playlist: http://bit.ly/2EcbaKf
Clips playlist: http://bit.ly/2JYkbfZ

EPISODE LINKS:
- Jeremy Twitter: https://twitter.com/jeremyphoward
- fast.ai Twitter: https://twitter.com/fastdotai
- fast.ai Web: https://www.fast.ai/
- fast.ai Course: https://course.fast.ai/

OUTLINE:
0:00 - Introduction
1:18 - First program
3:07 - Favorite programming languages
15:01 - Programming languages for machine learning
23:35 - Fast.ai intro (to be continued later)
24:31 - Ai and deep learning in medicine
32:30 - Privacy
37:55 - Fast.ai
40:42 - Theory vs practice
45:43 - DAWNBench - Stanford deep learning benchmark
56:24 - Fusing multiple audio and image sources
59:01 - Learning rate & deep learning as an experimental science
1:04:32 - Working with data
1:06:16 - Deep learning cloud options
1:09:12 - Deep learning frameworks
1:17:51 - How long does it take to finish fast.ai courses?
1:19:49 - Lessons from teaching deep learning
1:21:34 - Advice for people starting with deep learning
1:27:02 - Startups and entrepreneurship
1:32:21 - Anki and spaced repetition
1:40:06 - Next breakthrough in deep learning
1:41:17 - Job displacement and Andrew Yang

CONNECT:
- Subscribe to this YouTube channel
- Twitter: https://twitter.com/lexfridman
- LinkedIn: https://www.linkedin.com/in/lexfridman
- Facebook: https://www.facebook.com/lexfridman
- Instagram: https://www.instagram.com/lexfridman
- Medium: https://medium.com/@lexfridman
- Support on Patreon: https://www.patreon.com/lexfridman

Professor Daniel Willingham describes research showing that learning styles are a myth.
Added closed captions!
For more info, see this link: http://www.danielwillingham.co....m/learning-styles-fa

What is Machine Learning?
Traditional programming requires human to define set of instructions
which requires a tons of code and leave a plenty of room for error.
With machine learning, we just need data, a tons of data to be precise.
Lucky for us, thanks to internet and smartphones, we have a tons of data.
In machine learning, instead of following hard coded instructions, a program can learn from data or adapt its behavior according to experience.

We can divide Machine Learning into three broad categories.
Supervised learning, Unsupervised learning and Reinforcement learning.

Please Like and Subscribe for more weekly videos!

Follow me on Twitter: https://twitter.com/thecompscirocks
Follow me on Instagram: https://www.instagram.com/thecompscirocks/
Follow me on Facebook: https://www.facebook.com/thecompscirocks/

Some sources & further reading:
https://www.mathworks.com/solu....tions/machine-learni
http://www.r2d3.us/visual-intr....o-to-machine-learnin
https://en.wikipedia.org/wiki/Machine_learning
https://en.wikipedia.org/wiki/Supervised_learning
https://en.wikipedia.org/wiki/....Unsupervised_learnin
https://en.wikipedia.org/wiki/Cluster_analysis
https://en.wikipedia.org/wiki/....Reinforcement_learni

NSynth Super is an open source experimental instrument. It gives musicians the ability to explore completely new sounds generated by the NSynth machine learning algorithm.

Learn more at https://g.co/nsynthsuper

Фрагмент мастер-класса №2 "Внедрение электронного обучения"

Подробнее о летних мастер-классах про e-learning в Алматы:
http://www.elearningkz.org/

Take TESOL online courses to learn how to teach English as a foreign or second language: https://www.integrating-techno....logy.org/enrol/index

You may find the latest research studies on child language acquisition/learning by Patricia Kuhl of interest http://ilabs.uw.edu/institute-....faculty/bio/i-labs-p

Want to stay current on emerging tech? Check out our free guide today: http://bit.ly/2GJesc2

What is AI? What is machine learning and how does it work? You’ve probably heard the buzz. The age of artificial intelligence has arrived. But that doesn’t mean it's easy to wrap your mind around. For the full story on the rise of artificial intelligence, check out The Robot Revolution: http://hubs.ly/H0630650

Let’s break down the basics of artificial intelligence, bots, and machine learning. Besides, there's nothing that will impact marketing more in the next five to ten years than artificial intelligence. Learn what the coming revolution means for your day-to-day work, your business, and ultimately, your customers.

Every day, a large portion of the population is at the mercy of a rising technology, yet few actually understand what it is.

Artificial intelligence. You know, HAL 9000 and Marvin the Paranoid Android?

Thanks to books and movies, each generation has formed its own fantasy of a world ruled -- or at least served -- by robots. We’ve been conditioned to expect flying cars that steer clear of traffic and robotic maids whipping up our weekday dinner.

But if the age of AI is here, why don’t our lives look more like the Jetsons?

Well, for starters, that’s a cartoon. And really, if you’ve ever browsed Netflix movie suggestions or told Alexa to order a pizza, you’re probably interacting with artificial intelligence more than you realize.

And that’s kind of the point. AI is designed so you don’t realize there’s a computer calling the shots. But that also makes understanding what AI is -- and what it’s not -- a little complicated.

In basic terms, AI is a broad area of computer science that makes machines seem like they have human intelligence.

So it’s not only programming a computer to drive a car by obeying traffic signals, but it’s when that program also learns to exhibit signs of human-like road rage.

As intimidating as it may seem, this technology isn’t new. Actually, for the past half-a-century, it’s been an idea ahead of its time.

The term “artificial intelligence” was first coined back in 1956 by Dartmouth professor John McCarthy. He called together a group of computer scientists and mathematicians to see if machines could learn like a young child does, using trial and error to develop formal reasoning. The project proposal says they’ll figure out how to make machines “use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.”

That was more than 60 years ago.

Since then, AI has remained for the most part in university classrooms and super secret labs … But that’s changing.

Like all exponential curves, it’s hard to tell when a line that’s slowly ticking upwards is going to skyrocket.

But during the past few years, a couple of factors have led to AI becoming the next “big” thing: First, huge amounts of data are being created every minute. In fact, 90% of the world’s data has been generated in the past two years. And now thanks to advances in processing speeds, computers can actually make sense of all this information more quickly. Because of this, tech giants and venture capitalists have bought into AI and are infusing the market with cash and new applications.

Very soon, AI will become a little less artificial, and a lot more intelligent.

Now the question is: Should you brace yourself for yet another Terminator movie, live on your city streets?

Not exactly. In fact, stop thinking of robots. When it comes to AI, a robot is nothing more than the shell concealing what’s actually used to power the technology.

That means AI can manifest itself in many different ways. Let’s break down the options…

First, you have your bots. They’re text-based and incredibly powerful, but they have limitations.

Ask a weather bot for the forecast, and it will tell you it’s partly cloudy with a high of 57. But ask that same bot what time it is in Tokyo, and it’ll get a little confused. That’s because the bot’s creator only programmed it to give you the weather by pulling from a specific data source.

Natural language processing makes these bots a bit more sophisticated. When you ask Siri or Cortana where the closest gas station is, it’s really just translating your voice into text, feeding it to a search engine, and reading the answer back in human syntax. So in other words, you don’t have to speak in code.



Machine intelligence, artificial intelligence, machine learning, artificial intelligence tutorial, machine learning tutorial, evolution of machine learning, advantages of artificial intelligence, applications of artificial intelligence, ai meaning, machine learning applications, artificial intelligence examples,

Thanks to HelloFresh for sponsoring today's video! Get $60 off your first 3 boxes: https://bit.ly/2S53YXd and use promo code "imalittlestinker60"

Everyone and their mother has a reaction channel on youtube in 2019... but can I be the best? Let's watch some of the most popular ones and see if we can learn their secrets.

No hate to the people in this video, this is just for fun. There are a lot worse things happening online that are a lot less fun to talk about.

buy my merch:
https://www.drewgoodenshop.com/

follow me:
twitter - https://www.twitter.com/drewisgooden
instagram - https://www.instagram.com/drewisgooden
twitch - https://www.twitch.tv/drewisgooden

5 fortnite youtubers who've tried not to DIY challenge

We know how to help kids develop into powerful learners. Now, we just need to make that happen in schools.

"A parent of two teen-agers, Will Richardson has spent the last dozen years developing an international reputation as a leading thinker and writer about the intersection of social online learning networks and education.

Will has authored four books (with two more on the way), including ""Why School? How Education Must Change When Learning and Information are Everywhere"" (September, 2012) published by TED books and based on his 2013 TEDx talk in Melbourne, Australia. ""Why School?"" is now the #1 best-selling TED book ever.

A former public school educator of 22 years, Will is also co-founder of Modern Learner Media and co-publisher of ModernLearners.com which is a site dedicated to helping educational leaders and policy makers develop new contexts for new conversations around education.

Will lives in rural New Jersey with his wife Wendy and his kids Tess and Tucker."

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx