7 Images That Will Inspire Both Novice and Pro Coders

Coding is an amazing ability — and it is becoming an increasingly important skill for all professionals to understand as we evolve into a digital world. Learning to code requires logic, creativity and (above all) a lot of patience. Whether you’re a novice or a pro coder, it’s important to stay inspired and remember why you began learning in the first place. Read on for our favorite motivational images for coders.

1. Coding offers job opportunities galore — and parents agree!

2. The late Stephen Hawking offered his wisdom on the importance of coding.

3. Unlocking new possibilities begins with the press of a button.

4. What will you create? The opportunities are endless and vary depending on your unique perspective — give the gift of your ideas to the world.

5. Although coding is heavily math-based, it also takes creativity to turn a vision into a reality.

6. Want to change the world? Code.

7. Taking an abstract thought from your mind and weaving it into a logical formula for the world to see is one of the many incredible abilities of a coder.

Advanced Machine Learning Techniques: Principal Component Analysis

By Camille D., Age 17

This article will focus on a method data scientists and programmers use to make data easier to explore, visualize, and interpret data, called principal component analysis (PCA). The explanations in this article assume some background in linear algebra and statistics.

PCA is based on dimensionality reduction: “the process of reducing the number of random variables under consideration by obtaining a set of principal variables,” in other words, transforming a large dataset into a smaller one without extracting too much key information. This process is considered expensive for machine learning algorithms; a little accuracy must be traded for simplicity. Minimizing this cost is part of the job for PCA.

The first step of PCA is standardization, the process that is the least mathematically involved. Standardization takes care of the variances within the initial variables, specifically with regards to their ranges. For example, the value of one variable may lie within the range of 0 to 10, and the value of another within the range of 0 to 1. The variable whose possible value lies between 0 and 10 will carry a greater weight over the second variable, leading to biased results. Mathematically, this can be addressed by subtracting the dataset’s mean from the value of the variable and dividing this result by the set’s standard deviation.

After standardization is performed, the values of each variable will all be within the same range.

Note that standardization is different from normalization in descriptive statistics. Normalization rescales the values into a range from 0 to 1, while standardization rescales the dataset to have a mean of 0 and a standard deviation of 1.

In almost any case, of course, this will yield a value smaller than 1.

The second step, covariance matrix computation, is where things unfortunately begin to get more complicated. We first must understand the definition of covariance: “a measure of how much two random variables vary together.”

**Covariance differs from correlation in that correlation describes how strongly two variables are related, while covariance indicates the extent to which two random variables change with one another. The values of covariance lie between -∞ and ∞, while the values of correlation lie between -1 and 1. Correlations can be obtained only when the data is standardized.

Covariance matrix computation aims to investigate how the variables in the input dataset are related to one another. This is important because it helps detect redundant information that may come from a high correlation between two elements. We compute a covariance matrix to determine these correlations. The covariance matrix is an nn matrix, where nis the number of dimensions, that has entries of all possible covariances within the dataset.

A couple notes:

Cov(x,x)=Var(x), or the variance of the initial variable.
The Cov()operator is commutative, so Cov(x,y)=Cov(y,x), so the upper and lower triangular portions of the matrix are equal.

The covariance matrix is simply an organization that lists the correlations between all possible pairs of variables. The sign of the value of the covariance is what tells us about the correlations between elements. If the covariance is positive, then the two variables are directly correlated. If the covariance is negative, the relationship between the two variables is an inverse correlation.

The next step in PCA is actually identifying the principal components by computing the eigenvectors and eigenvalues of the covariance matrix. However many principal components are produced from the dataset should be equal to the amount of dimensions in the set. Principal components are “combinations” or “mixtures” of the initial variables, and are constructed such that each of them are uncorrelated and as much information from the variability initial variables as possible is stored in the first component, and the succeeding components account for the remaining information, as shown in the example plot below for an 8-dimensional dataset:

This form helps significantly with dimensionality reduction because it eliminates components with little to no information while still retaining the information that describes the key relationships within the data. Consider the dataset below:

The direction first principal component line represents the direction of the highest variability in the data. Since the variability is the largest in the first component, the information captured by the first component is also the largest. It’s the line in which the projection of the points onto the line is the most spread out. This line maximizes the average of the squared distances from the projected points to the origin. The direction of the second principal component line should be orthogonal in order for the principal components to be completely uncorrelated.

We continue to calculate principal components n times, where n is the original number of values in the dataset.

Going back to eigenvectors and eigenvalues, here are a couple preliminary notes about eigenvectors and eigenvalues:

Every eigenvector has its own corresponding eigenvalue.
The number of eigenvectors and corresponding eigenvalues is equal to the number of dimensions/variables in the data.
For a tutorial on how to calculate the eigenvalues and eigenvectors of a matrix: https://www.scss.tcd.ie/~dahyotr/CS1BA1/SolutionEigen.pdf.

The eigenvectors of the covariance matrix give the directions of the principal component axes, and the eigenvalues are coefficients for the eigenvectors, and give the scalar amount of variance within each PC. The PCs in order of significance can be obtained by ranking the eigenvalues for each eigenvector from highest to lowest. To get the percentages of the variance carried by each PC, divide each of eigenvalue by the sum of all eigenvalues.

Next, we have to determine whether we want to keep some of the lesser components (the ones with low eigenvalues). We form a matrix called the feature vector with the eigenvectors of the components we do keep. This demonstrates the concept of dimensionality reduction since we are subtracting from the initial amount of principal components we had, which is equal to the dimension of the original dataset.

Lastly, we use our feature vector to restructure our dataset in a sense. We want to put our data in terms of the axes given by the principal components instead of the original axes. We can do this pretty easily by multiplying the transpose of the feature vector by the transpose of the original dataset.

Four Ways Video Games Help People

Video games. If you are an avid gamer yourself, then you know the excitement and joy that comes with playing your favorite game. In fact, many gamers decide they love the interactive entertainment so much that they not only want to play — they want to create! Video game programming and design can be an incredible outlet for bringing both coding and creativity to life, while providing a source of entertainment that truly helps people. Yes, you read that correctly — video games can help people. Read on to learn how.

Improves brain function

Scientific research has discovered that video games improve brain function. According to research published in Frontiers in Human Neuroscience, partaking in video games increases attentiveness in several different areas — including sustained attention. Additionally, the same study found that gamers are more efficient in general attention activities, which can positively impact one’s day-to-day life.

Relieves stress

You’ve had a long, stressful day at work or school and to you, nothing beats sitting down and playing Call of Duty or World of Warcraft. It’s vital in our modern society to have an outlet to destress, and video games are a perfect medium to let the problems of the real world melt away. A Dale TV survey showed that 55 percent of gamers agree with that assessment. Additionally, 47 percent of respondents in the same survey believe playing games positively affects their lives. That sounds like a win-win.

Opens a cool career path

If you decide to get into a career making amazing games, you may even inspire MORE people to seek a career making amazing games too — and the cycle of creativity continues on! It’s natural for those playing video games to wonder, “how do these games work?” That curiosity can lead to an amazing career in coding, and that’s just the beginning. When one decides to venture into the world of coding, a host of career opportunities opens. From software development to computer programming to business intelligence analysis, coding provides you the tools to opt for a rewarding career in just about any industry. To think, this can all begin from playing video games.

Promotes social skills

According to the American Psychological Association (APA), video games of all genres may positively affect children’s social skills in addition to boosting their learning and health. But beyond science, those of us in the know, understand that video games are a social event. You sign online and interact with others and even learn how to interact as a team.

Video games are great for entertainment but as we have just learned, they can also positively impact people’s lives. Whether it helps you relieve stress or leads to an amazing career, video games are incredible.

Spring Cleaning Tips for Your Home Study Area

It’s time to say goodbye to frigid temperatures and blowing snow and welcome warm sunshine and tranquil breezes. Spring is the time of year that marks new beginnings, so it makes perfect sense to shake off the chill of winter and put your best foot forward. And can you really say you’re giving the world your best if your study area looks like it endured a blizzard or two over the past few months? We’re going to help you clean up your act and make your study area look as pristine as a freshly bloomed tulip.

Clean but don’t overwhelm yourself

If your study area isn’t too cluttered or untidy, this section doesn’t apply to you. However, if your home study area is an absolute disaster, please take note. When attempting to spring clean your study area, or anything else for that matter, don’t overwhelm yourself. Make a cleaning plan and take your time. If your spring-cleaning efforts encompass a day, or two, or even three don’t fret. Just get the job done right.

Declutter and organize

More clutter equals more distractions and when you’re trying to be serious about your work, distractions are your worst enemy. Remove the unnecessary trinkets and decorations that do nothing more than sway your focus and only add items that won’t act as the proverbial shiny object. Furthermore, get rid of piles of paperwork and books and organize them in a file cabinet or bookshelf. Try to have a system so you can find important papers. The toss to the side and forget them method will only serve to frustrate you in the future.

Clean

This is spring cleaning, after all, so the actual cleaning part does have to occur. While you are decluttering and organizing, break out the vacuum, broom and dust cloth. Before adding items back to your study area, make sure everything is tidy and dust free. Vacuum around (and under) your desk and try to deep clean. You want to welcome in this beautiful time of year with a beautiful study area.

Add some life and color

Although you don’t want too many distractions, you also don’t want your study nook to feel drab and boring. After you have completed your cleaning, decluttering and organizing efforts, add a bit of color with a painting or a vibrant vase of flowers. You want to set an upbeat mood before and during your study time. The quest for knowledge doesn’t have to dull and colorless.

Upgrade

If it fits into your budget, a new desk or computer can really give your study efforts a nice morale boost. You can also spruce up your study area without breaking the bank. A nice used bookshelf or cool vintage lamp can provide a new look on a budget. Just remember to keep your new and old equipment and furniture clean.

Maintain

Once everything is clean and ready to roll for countless successful study sessions, do your best to maintain. Set a weekly time to dust and vacuum. Additionally, consider continually organizing so the next time you decide to perform a deep clean, you won’t have nearly as much work. You’ll thank yourself.

A clean study area won’t guarantee an A+, but it can at least make your work more pleasurable. So, don’t be afraid to bring out your cleaning supplies and get to work. We’ll give you an A+ for effort.

4 Tech-Savvy Skills to Learn

It’s no secret that having technical savvy can go a long way in furthering your career or helping you land a job. But do you know which skills can set you apart from the competition and improve your chances of being a superstar at work? You are about to discover four vital areas you need to master to become the envy of coworkers and the apple of your boss’s eye. You’ll even impress yourself.

Keyboard shortcuts

Your mouse can come in handy, but don’t let that little gadget get in the way of increased efficiency and productivity. It’s time to reduce your mouse habit and learn the secret most advanced computer users know, keyboard shortcuts are awesome. You probably already know shortcuts like Ctrl+C and Ctrl+V (well hopefully anyway) but there is a whole tech-savvy world filled with shortcuts you haven’t even imagined. Research and discover the plethora of keyboard shortcuts that will make your mouse almost seem unnecessary.

Coding

Even if you consider yourself a bit technologically challenged, you can learn how to code. It may seem intimidating but it’s not when you find the right teacher. An excellent coding school can set you on a path to learning the ins and outs of creating incredible apps and software. And if you’re not interested in discovering the next big thing in mobile applications, having at least a basic understanding of code can help you become a better business owner or employee.

Microsoft Office

Like it or not, most office workers will need to delve into the productivity staple known as MS Office. For instance: When your boss wants a stellar presentation on your newest project, what do you turn to? PowerPoint. Did your coworker just send you a file filled with raw data? It’s time to open Excel. Oh, and speaking of that email you received from your coworker, you probably used MS Outlook to open it. You don’t have to be an expert at Office, but in today’s working environment, having at least an intermediate grasp is vital. If you feel uncomfortable learning Office on your own, find an instructor or school that can help educate you on this important software solution.

Improved typing

In the past, typing was a nice skill to have, in our present day, it’s a must. But it’s a skill we tend to learn and then fail to hone as time passes by. Don’t allow this to occur. Improving your typing speed, and accuracy can skyrocket your productivity. Admit it, how many times have you backtracked because you made an error in your presentation or article? Maybe, you still need to look at your keyboard from time to time. There are classes, apps and even games that can break you free from mediocre typing and help you become a keyboard master.

With an investment in time, and a little effort, you can master these four vital skills. Just be forewarned, once you do, you’ll be in high demand. Hopefully you won’t forget the little people.

How Face Filters and Face Recognition Work

By Mira B., Age 14

Many people use social media apps such as Instagram or Snapchat, which have face filters for people to take and post pictures of themselves. But many people do not realize how these filters are created and the technology behind how they fit people’s faces almost perfectly. The mechanics behind face filters was originally created by a Ukrainian company called Looksery; they used the technology to photoshop faces during video chats. Snapchat bought their algorithm, called the Viola-Jones algorithm, and created the face filters seen in many social media apps today.

Creating face filters is more difficult than you may think, so I’ll break it down into five key steps:

The first step is face detection. The image is initially viewed in ones and zeros, so the algorithm scans the image, looking specifically for color patterns. This can include finding that the cheek is lighter than the eye or that the nose bridge is lighter than surrounding areas. After detecting these patterns, a face can be distinguished in the camera.

The second step is the landmark extraction. Using specific algorithms in a 2D image, facial features such as the chin, nose, forehead, etc are determined.

The third step is face alignment. The coordinates of landmarks on people’s faces are taken to properly fit the filter to a particular face.

The fourth step is 3D mesh. Using the 2D image, a 3D model of the user’s face is built to fit the filter animation to a specific face.

The last step is face tracking, which approximates and locates the 3D mask in real time. This allows the user to move their face without the filter disappearing or moving to an incorrect location.

Another way to think of these steps is to imagine a human body. The landmarks identified in a 2D image serve as the skeleton for the future mask. Similar to how bodies differ in shape, so do people’s face structures. Using face alignment, the filter matches with the coordinates of landmarks from a certain face. People’s skin makes them look the way they are and 3D mesh step is like aligning the skin to the skeleton. Similar to how bodies move while keeping the skeleton, skin and muscle together, face tracking follows the face to make sure the filter stays on the right coordinates.

Why Now is the Best Time to Learn How to Code

You’ve been working from home for weeks, just about every recreational activity you normally enjoy is closed and your choices for entertainment are starting to dwindle. Finally, when pacing around your house and walking the dog for the 10th time is no longer an option, you figure it’s time to tackle a new challenge. But what are you going to do? Why not try to learn a cool new skill? Quite frankly, there is no better time to dust off your hippocampus and become a student. And there is no better skill to learn than coding. Here’s why.

Coding is cool

We may be biased when it comes to this opinion, but coding is downright cool. You get to be a member of a technological community that creates amazing things like apps, games, software and websites. Not only do you get to create but you also have access to the latest cutting-edge technology. Admit it, what part of that doesn’t sound cool?

Coding makes your resume more appealing

Instead of binge watching another crazy documentary on your favorite streaming service, why not make your resume pop? When you can feature an appealing skill like coding on your resume, hiring managers will take notice. Furthermore, if you are looking to change careers entirely, coding allows you to consider job opportunities you couldn’t have in the past. Occupations that allow you to create and have fun.

Increase your earning potential

When you can boast having coding skills, you’ll earn more money. According to one study conducted by Course Report, graduates of coding bootcamps enjoyed a 44% increase in their salaries. Investing an hour or two a day to learning this amazing skill can pay off.

Coding careers are flexible

From flexible working hours to the ability to work anywhere you’d like, a career in coding enables you to work and live the way you want. As current circumstances have taught us, the ability to perform your job functions from home is not just a luxury but during challenging times can be a real lifesaver. And when life returns to normal, working from an exotic beach doesn’t sound too shabby either.

More time for side projects

You have dreams that go well beyond your occupation, and when you have a flexible schedule you can pursue those aspirations. Whether you have a great idea for an app that will revolutionize an industry or even a business idea that isn’t specifically related to coding, your new skill will greatly increase your chance of success. Feel free to dream big.

These were just five reasons to help convince you that right now is a great time to learn coding. You can probably think of countless more. So, what are you waiting for? Start learning.

Tips for Teaching or Tutoring Your Kids At Home

Teaching children, although rewarding, is not an easy task. It requires patience, an eye for detail and the ability to stay calm when the learning process goes sidewise. So how does a parent who doesn’t have the formal education to instruct children take up the reigns and become a teaching superstar? We’ll go over five tips that will give you guidance in teaching your children coding or any other subject. You’ll just have to provide the patience.

Succeed by planning and scheduling

There’s a theme when it comes to doing just about any task, plan and schedule. Although you have heard it a thousand times, it’s always worth repeating. Before you teach or tutor your children, craft a lesson plan and schedule. If you are teaching your children in place of school, try to adhere to a normal school day routine. Be specific in your planning and ensure there is enough time to tackle all the subject matter you have scheduled for the day. If only one subject is on the agenda, say like coding, most of your efforts will be in the planning phase rather than scheduling. However, regardless of the number of subjects, put effort into your planning.

Meet with your children

Sometimes a meeting can’t be an email. Meet with your children and discuss the day’s lesson plan. Talk over expectations and give them a clear idea of what they will be learning. Utilizing a visual aid, like a tablet or the old-fashioned route, a whiteboard, can help your children see what the day will have in store. There is no need for surprises when it comes to learning.

Take suggestions

Education should be an interactive process. Ask your children for suggestions on everything from lesson plans to teaching techniques. Discovering how your children learn will lead to more success. Which in turn will make your job as the teacher much simpler.

Ask for help

Do you have a friend or acquaintance who is a teacher? If you do, fabulous, because you have someone who has the knowledge and experience to lend you a helping hand. Don’t be afraid to ask for help when you feel stuck or confused. Advice from a professional can give you that boost of confidence to become an awesome at home teacher.

Don’t forget the breaks

You may want to power through the subject matter at breakneck speeds but remember, you are teaching children. This is especially true if you are teaching an entire course load of material. Schedule enough time for breaks and don’t forget the food and drinks. Nutrition is vital for young learners

Teaching your children may be challenging but it’s not as daunting when you are prepared. Plan, schedule and allow your children to provide input. With some effort and an investment in time, you and your children will enjoy the entire process. You may not even need as much patience as you originally thought.

Tips for Learning While at Home

You think you have a solid, at-home learning plan but it soon becomes derailed by a litany of distractions and obstacles. It can be quite frustrating. Learning at home has its fair share of challenges, but it also boasts plenty of pluses. If you formulate a proper plan and make a few tweaks to your learning environment it can be a rewarding experience. We promise. Here are 5 tips that will help you become an A+ home learner.

Craft a relaxing and efficient study space

There are easy options when it comes to spaces for learning at home, such as the dining room table or a desk in the middle of the family action, but these are rarely the best choices. Although these areas can work, you want the best possible space to learn effectively. Find a location that is not only comfortable but also allows you to focus with minimal distractions. Good old-fashioned trial and error can be utilized to find the ideal learning space.

Have a plan and be organized

Learning can be exciting, so, understandably, getting down to work immediately sounds like a fun idea. But rushing into your studies without having a plan will greatly reduce your chances for success. Instead, take time either the night before or early morning to create a learning plan. Additionally, keep your learning space organized and clean. Don’t let clutter get in the way of being a superstar student.

Dress for success

It’s an enticing proposition; learning while remaining in your PJs for the entire day. Although, there is an inherent comfort with learning from home, forgoing PJs and opting for something more appropriate for daytime hours can boost your learning potential. You don’t have to dress as if you are going to a job interview, but a comfortable pair of pants and a nice shirt can do wonders for your attentiveness and confidence.

Set goals

How do you know if you are making progress if you don’t set goals? Well, you won’t know. That’s why goal setting is a vital step in the at home learning process. Like how you produced a learning plan in the previous tip, allot time to craft short- and long-term goals. You can have daily, weekly, monthly and even yearly goals. Make them challenging but not too difficult. You want to set yourself up for success.

Take breaks

Yes, even learning from home requires a student to step away and take a break. When you plan for the day ensure that you leave time for at least one 15-minute break. During this breaktime, you should push your studies to the side and focus on something entirely different. It can be reading a book, reading emails or even housework. The key here is to give your mind a break from learning and recharging for another round of studying.

Learning from home can be comfortable, rewarding and fun when you follow these 5 simple tips. Now the only thing you have to prepare for is your exceptional success.

The Julia Language – A New Pillar of Scientific Computing

By Camille D., Age 17

Developed in 2009 and made available in 2012, Julia is one of the fastest-growing languages in the industry. As it routinely makes an appearance in language popularity rankings, there is a potentiality for the language to outshine languages such as Python in the realm of computational science and general programming.

Julia was created by Jeff Bezanson, Stefan Karpinski, Viral B. Shah, and Alan Edelman, with a collective desire to unify the best amenities of all the big languages, from the “speed of C” to the “dynamism of Ruby.” It was crafted with flexibility and versatility in mind – the language boasts the ability of its users to “write an algorithm … and apply it to an infinite lattice of types.”

No language is perfect; you are always making a trade-off when choosing a language to learn. A C++ pupil will enjoy the language’s high speed, but will miss out on the straightforwardness and garbage collection capabilities of Java. There will never be such thing as a language that will solve every issue or be free of any shortcomings whatsoever. Nonetheless, programming languages have evolved rapidly, and Julia exemplifies how far they have come. Here are a few reasons to choose Julia.

Julia is fast and high-performing. Applications created with Julia use the LLVM Compiler Infrastructure to efficiently compile the code to machine language for multiple different platforms. When writing code in a compiled language, you must explicitly define the types of variables you will use and the operations intended to be performed on them. Since the hardware will know exactly what to do as a result, the code will be executed quickly and efficiently. On the other hand, the CPU does not have a concept of the “variables” you use when writing in an interpreted language. The interpreter must provide instructions to the CPU about what the variables contain (i.e. int vs. float data type), forcing the CPU to wait. This is what makes interpreted languages slow relative to compiled languages such as C. Julia falls somewhere in the middle of the spectrum of compiled and interpreted languages. Julia’s compiler doesn’t have to have the information previously mentioned, but it is prepared for when a function is called and acquires all the material promptly. From the information provided, the compiler puts together fast and precise CPU instructions.

Julia is packed with immense capabilities in data science and numerical computing. When using Julia, it is evident that conventional mathematics become closely bound with programming. The Julia REPL (a programming environment in which a user types in a command and can easily see the result of their command) gives access to symbols often used in mathematics, including Greek letters and subscripts. The symbols are inserted by typing a backslash \, followed by a string corresponding to the character. For example, entering “\Gamma” will return the Gamma symbol Γ.

A rather unique feature that comes with Julia is function composition, which is achieved by the operator (∘). For example, writing (sqrt ∘ *)(5, 2) will multiply two numbers, 5 and 2, and then find the square root of the result. Julia is also packed with external call support, and can link with a throng of languages including Python, Java, C++, and R. Python applications can call Julia through PyJulia, and R applications can call it through through its interface, JuliaCall.

Julia is versatile, which is the principal reason why it is so ahead in the game. It provides a wealth of tools and frameworks for deep learning, data visualization, and graphs, and capabilities for clustering, trees, and generalized linear models. Even with a seemingly infinite capacity for mathematical transformations, however, Julia is excellent for general programming, as users can write UIs, statically compile code (even though it is generally dynamic – types of variables aren’t known until runtime), and deploy it on a webserver.