In one sentence, describe what the following article is about: One of the easiest ways to do this is to apply artist-quality Gesso, a thick gel-like primer. Apply it like paint, or spread it around with a palette knife, if it's thick enough. This will allow you to control the style of the texture. You could also leave the canvas smooth and blank. Again, there are no rules for abstract art saying you must have a textured background. Many artists simply start painting on a blank canvas. Use blue painter's tape and place several lines, creating geometric shapes, such as triangles, squares, and rectangles. The goal is to create images that aren't representative of reality. The taped lines will help you paint Painter's tape will ensure that your painting has crisp, clear lines and shapes. Use rulers and pencil lines instead of tape. If you don't want to deal with the gaps that the painter's tape will cause when you remove it, try marking your canvas using a ruler and pencil. Again, lay your ruler down across several points to create geometric shapes. Decide which colors you'll be using to complete your painting. Mix them on an artist's palette or plate. You could also mix the colors directly on the canvas, but this will take away some control over the finished look. Don't worry if you happen to get paint on the painter's tape. Also, don't feel as though you must fill your entire canvas, or all of the shapes, with color. Some abstract artists will outline the colors of each shape before they begin painting. Others simply paint and decide which colors to use as they go along. As soon as you've decided the painting is complete, remove the painter's tape. If you'd like crisp, clear edges, remove the tape while the paint is still wet. If you remove the tape from a dry painting, it's liable to pull paint away with it, creating slightly rough edges. Once you remove the tape, you'll notice white lines from where the tape was covering the canvas. While you can leave it, you could also paint the lines in.
Summary: Create a textured background. Tape lines at intersecting points across the canvas. Mix your paint colors. Paint in the spaces between the tape. Remove the tape. Fill in the blank space from the tape, optional.

In one sentence, describe what the following article is about: It is rarely necessary to soak apples or use ingredients other than tap water or vinegar to wash them. Fancy waters that involve soaking apples can change their taste. Stick to tap water for the most part, and vinegar if your apples are very dirty. Elaborate washes will do little to clean apples. Many people think organic apples do not need to be washed. While organic apples use fewer pesticides, they are still prone to environmental bacteria and can be contaminated during transport. Even organic apples should be washed under tap prior to eating. Moldy produce does not have to be discarded if only a small corner is infected with mold. If you see a small part of your apple is moldy, cut away that portion with a knife. Unless an apple is completely covered in a layer of fuzzy mold, there is no need to throw it away.
Summary: Avoid fancy washes. Wash apples even if they're organic. Do not automatically throw out moldy produce.

In one sentence, describe what the following article is about: Numbers are what a data analyst works with every day, so you want to make sure you’re comfortable with math. Having a firm understanding of college algebra is important; you should know how to do things such as interpret and graph different functions as well as work through real life word problems. Knowing multivariable calculus and linear algebra will help as well. To become a data analyst, you’ll need to be able to interpret data, which is where statistics comes in. Start with a foundation of high school- or college-level statistics, and then move on to more challenging information that might be required for the job.  Mean, median, and mode, as well as standard deviation, are examples of the kinds of statistics concepts you would learn in high school or college. Having a strong grasp of both descriptive and inferential statistics will be helpful as well. While you don’t need to be an expert at coding or programming to start off as a data analyst, you should be comfortable doing it on a small level. Start by learning how to use programs such as Python, R, and Java first, and then work your way up to others.  SQL programming is another that is common among data analysts. You can take courses online to learn coding and programming. Once you’ve analyzed your data, you’ll need to be able to talk about it with others. Work on being able to explain complicated information in a way that makes non-data analysts understand your findings, and practice using programs that illustrate the data in a visually-helpful way. You should be able to communicate data visually as well as verbally. Understand how to use tools such as ggplot and matplotlib to illustrate your findings. You’ll be organizing data and calculating numbers as a data analyst, so you need to be comfortable using Excel. There are many video tutorials online, as well as free sites, that will help teach you all you need to know about using Excel to its full potential. Teaching a computer to come up with predictions or decisions on its own after it has studied data, or machine learning, is important when dealing with data analysis. Look online to find courses you can take that will teach you all you need to know about machine learning, and some of them are even free.  To understand machine learning, you'll need to have a foundation in programming and statistics. There are three types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. An example of supervised learning is your email filtering your inbox and putting spam in its own folder. Supervised learning would be when Netflix suggests television shows or movies that you might like, and an example of reinforcement learning is a self-driving car and its ability to see and then adapt to its surroundings.
Summary:
Master college-level algebra. Understand statistics. Work on your coding and programming abilities to be a more appealing candidate. Develop strong communication and presentation skills. Familiarize yourself with Microsoft Excel. Learn about machine learning.