In addition to surprises being fun, many of the videos are basically toy commercials. This video of a person pressing sparkly Play-Doh onto chintzy Disney princess figurines has been viewed million times. They get to choose what they watch. And kids love being in charge, even in superficial ways. Rich and others compare the app to predecessors like Sesame Street , which introduced short segments within a longer program, in part to keep the attention of the young children watching.
For decades, researchers have looked at how kids respond to television. It makes sense that researchers have begun to take notice. In the mobile internet age, the same millennials who have ditched cable television en masse are now having babies, which makes apps like YouTube Kids the screentime option du jour. Instead of being treated to a minute episode of Mr. But toddlers and preschoolers are actually pretty separate groups, as far researchers are concerned. A 2-year-old and a 4-year-old might both like watching Daniel Tiger, or the same YouTube Kids video, but their takeaway is apt to be much different, Kirkorian told me.
Children under the age of 3 tend to have difficulty taking information relayed to them through a screen and applying it to real-life situations. Many studies have reached similar conclusions, with a few notable exceptions. She and her colleagues found striking learning differences among what young children learned—even kids under 2 years old—when they could interact with an app versus when they were just watching a screen.
Other researchers, too, have found that incorporating some sort of interactivity helps children retain information better. One idea is that kids, especially, like to watch the same things over and over and over again until they really understand it. I watched the Dumbo VHS so many times as a little kid that I would recite the movie on long car rides. Apparently, this is not unusual—at least not since the age of VCRs and, subsequently, on-demand programming and apps.
Young kids are also just predisposed to becoming obsessive about relatively narrow interests. How to use it How to use it Everything below is an outline, and you should tackle the items in order from top to bottom. I'm using Github's special markdown flavor, including tasks lists to check progress. I'd appreciate your help to add free and always-available public sources, such as YouTube videos to accompany the online course videos.
I like using university lectures. Python for Data Structures, Algorithms, and Interviews! Intro to Data Structures and Algorithms using Python! Udacity free course : A free Python centric data structures and algorithms course. Data Structures and Algorithms Nanodegree! Udacity paid Nanodegree : Get hands-on practice with over data structures and algorithm exercises and guidance from a dedicated mentor to help prepare you for interviews and on-the-job scenarios.
Book List This is a shorter list than what I used. This is abbreviated to save you time. These chapters are worth the read to give you a nice foundation He's awesome. This book covers the same topics. It covered everything and more. Here are some mistakes I made so you'll have a better experience.
The Algorithm That Makes Preschoolers Obsessed With YouTube
You Won't Remember it All I watched hours of videos and took copious notes, and months later there was much I didn't remember. Read please so you won't make my mistakes: Retaining Computer Science Knowledge 2. Use Flashcards To solve the problem, I made a little flashcards site where I could add flashcards of 2 types: general and code. I made a mobile-first website so I could review on my phone and tablet, wherever I am. Make your own for free: Flashcards site repo My flash cards database old - cards : My flash cards database new - cards : Keep in mind I went overboard and have cards covering everything from assembly language and Python trivia to machine learning and statistics.
Take a break from programming problems for a half hour and go through your flashcards. Focus There are a lot of distractions that can take up valuable time. Why code in all of these? You'll see examples in books, lectures, videos, everywhere while you're studying. C Programming Language, Vol 2 This is a short book, but it will give you a great handle on the C language and if you practice it a little you'll quickly get proficient. Understanding C helps you understand how programs and memory work.
Just watch enough until you understand it. You can always come back and review. If some of the lectures are too mathy, you can jump down to the bottom and watch the discrete mathematics videos to get the background knowledge. Linked List vs Arrays: Core Linked Lists Vs Arrays video In The Real World Linked Lists Vs Arrays video why you should avoid linked lists video Gotcha: you need pointer to pointer knowledge: for when you pass a pointer to a function that may change the address where that pointer points This page is just to get a grasp on ptr to ptr.
I don't recommend this list traversal style. Readability and maintainability suffer due to cleverness. Implementing with array is trivial. Which on arrays? Which on both? I wouldn't recommend sorting a linked list, but merge sort is doable.
Interactive Video : Algorithms and Technologies - iqegumybiwyf.ml
Heap sort is great, but not stable. Sedgewick - Mergesort 5 videos 1. Mergesort 2. Bottom up Mergesort 3. Sorting Complexity 4. Comparators 5. Stability Sedgewick - Quicksort 4 videos 1. Quicksort 2. Selection 3. Duplicate Keys 4. Not required, but I recommended them: Sedgewick - Radix Sorts 6 videos 1.
Strings in Java 2. Key Indexed Counting 3. If you need more detail on this subject, see "Sorting" section in Additional Detail on Some Subjects Graphs Graphs Graphs can be used to represent many problems in computer science, so this section is long, like trees and sorting were. Tail Recursion video Dynamic Programming You probably won't see any dynamic programming problems in your interview, but it's worth being able to recognize a problem as being a candidate for dynamic programming.
This subject can be pretty difficult, as each DP soluble problem must be defined as a recursion relation, and coming up with it can be tricky. I suggest looking at many examples of DP problems until you have a solid understanding of the pattern involved. Know what NP-complete means. Computational Complexity video Simonson: Greedy Algs.
Long live testing. Is TDD dead? Introduction to Substring Search 2. Brute-Force Substring Search 3. Knuth-Morris Pratt 4. Boyer-Moore 5. Some have prefixes, some don't, and some use string instead of bits to track the path. I read through code, but will not implement. Sedgewick - Tries 3 videos 1. R Way Tries 2. Ternary Search Tries 3. Don't worry if most is over your head. The first half is enough. Expect to spend quite a bit of time on this. Look through the articles and examples. I put some of them below. How to ace a systems design interview Numbers Everyone Should Know How long does it take to make a context switch?
Just pick a few that interest you.
Practicing the system design process: Here are some ideas to try working through on paper, each with some documentation on how it was handled in the real world: review: The System Design Primer System Design from HiredInTech cheat sheet flow: Understand the problem and scope: define the use cases, with interviewer's help suggest additional features remove items that interviewer deems out of scope assume high availability is required, add as a use case Think about constraints: ask how many requests per month ask how many requests per second they may volunteer it or make you do the math estimate reads vs.
It's nice if you want a refresher often. Why you need to practice doing programming problems: problem recognition, and where the right data structures and algorithms fit in gathering requirements for the problem talking your way through the problem like you will in the interview coding on a whiteboard or paper, not a computer coming up with time and space complexity for your solutions testing your solutions There is a great intro for methodical, communicative problem solving in an interview.
You'll get this from the programming interview books, too, but I found this outstanding: Algorithm design canvas No whiteboard at home?
Why do you want this job? What's a tough problem you've solved? Biggest challenges faced? Ideas for improving an existing product. How do you work best, as an individual and as part of a team? Which of your skills or experiences would be assets in the role and why? Have questions for the interviewer Some of mine I already may know answer to but want their opinion or team perspective : How large is your team? What does your dev cycle look like? Are rushes to deadlines common?
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- 'Big data’ algorithm used to customize video game difficulty -- ScienceDaily.
- Table of Contents.
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- International History of the Twentieth Century and Beyond, 2nd edition.
- Get PDF Interactive Video: Algorithms and Technologies (Signals and Communication Technology).
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