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Machine Learning coined by Arthur Samuel in the 1950s is a subset of Artificial Intelligence that deals with algorithms, statistic models and analytics. Traditionally, machines were designed to follow certain instructions given to them and did not possess the ability to make decisions. Machine Learning changes this by being able to analyze, predict or classify various data to reach the optimal solution. Machine Learning enables a system to make statistically significant decisions based on the data collected during past interactions. Machine Learning makes way for a possibility wherein a system can gain intelligence over time.

In the digital age, Data is something that is abundantly available. The conventional way of programming is not the best solution to a problem involving pattern recognition or retaining a chunk of memory from a previous interaction. It gets complex and messy when trying to update for new requirements. Moreover, the traditional programming approach fails to handle a huge variety of data whereas, with Machine Learning, the more is always, the merrier. With the massive volume of data we generate, state-of-the-art Neural Nets models for easy pattern recognition are now possible.

Let’s have an example of some of the most common things we do almost every other day, like ordering food, groceries, or even clothes. All these now just a click away are powered by Machine Learning, which can find patterns and behaviors and learn from them without being explicitly programmed.

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The advent of ML technology has revolutionized our lives. They are so much blended into our daily routines that we mostly depend on them to accomplish our tasks. The smartphones that most of us cannot imagine our life without are majorly driven by Machine Learning. Right from unlocking the phone to using the various Social Media and e-Commerce apps installed, run on complex neural nets that are rigorously trained to give us a seamless usage.

In the ever-progressing world, Machine Learning is being recognized by several sectors for their betterment and to stand out amongst their competitors. Sectors such as Finance, Retail, Healthcare, Transport to name a few uses Machine Learning to reach out to more people and to create a personalized bond with them by taking into account their likes and dislikes.

Top Companies such as IBM, Google, Microsoft, Intel, Apple, Tesla, Facebook, Netflix, Instagram use Machine Learning effectively for reliable, fast and effective business decision making.

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The cool things that can be achieved with Machine Learning are what attracts everyone to this field. But what one fails to notice is that a lot goes into the background that makes an application driven by ML successful. Machine Learning is about how well you can communicate with the machine to get the work done.

Fluency in either Scripting Languages, i.e., Python or R, is essential. Contrary to popular belief, one does not need to be an established mathematician or statistician to start with Machine Learning. However, working knowledge on the basics is a must, the pre-defined libraries in programming Languages like Python and R can take care of the job pretty well. In addition, it is also necessary to take the rust off from one’s analytical skills since 80% of the time in building a successful ML model goes to analysis and selection of the right kind of data.

Machine Learning Tutorials are mainly targeted to grad students and working professionals like Analysts, Data Scientists or Developers who are assumed to have some prior knowledge on the fundamentals of Computer Science. However, the audience need not be limited to only this set of people. Anyone with basic analytical and programming skills and the right attitude and determination can ace Machine Learning.

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This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy PolicyUsing cording to finish the edges of your sewing projects definitely adds a professional quality, however it isn’t readily available in a wide variety of types or finishes which tends to limit its uses.

Making your own cording is not only fun, but it can be made in any color or thickness to coordinate with all your sewing projects. There are several ways to make your own cording, but machine wrapped cording, which is cording made using a sewing machine, is the quickest method. This type of cording is probably my favorite and I use it as a trim and also for embellishing and it can be used for all sorts of different ways.

Set up the sewing machine with the same thread on top and in the bobbin. This can be any color or type of thread as it won’t show once the cord is finished. Cut the base cording to the desired length. In this tutorial I’m demonstrating using three strands of 8 ply yarn which will produce approx 1/8″ diameter cording.

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Set the sewing machine for zigzag stitch wide enough for the needle to swing entirely over the yarn on either side. Length should be about 1.5 – 2.0.

Allow about 2-3 inches of cording to extend out the back of the machine, and holding the tail of the cord with your left hand and twisting the front section with your right hand, guide the cording under the foot. If it’s difficult to move the cord, loosen the tension on the presser foot if your machine has this option, or you may need to pull the cord slightly in order for it to feed through smoothly. Zigzag along the length of cording. This row of stitching will bind the separate pieces into one.

Shorten the length of the stitch to about .5, or shorter if you’re using fine thread, and holding the cording in the same manner as previous, satin stitch the length of the cording. This row of stitching helps to cover the base cord.

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Change the top thread and bobbin thread to the main color of the cord. Using the same stitch length, satin stitch the length of the cording. This is the finishing row of stitching.

If you want a bit of sparkle, finish the cord with metallic thread. Lengthen your stitch to 1.5 – 2.0, change to a metallic thread in the top and bobbin and zigzag the length of the cording.

If you sew a length of fine craft wire into the first or second row of stitching, you can make cording that you can shape and bend.Machine Learning Tutorial Machine Learning Applications Life cycle of Machine Learning Install Anaconda & Python AI vs Machine Learning How to Get Datasets Data Preprocessing Supervised Machine Learning Unsupervised Machine Learning Supervised vs Unsupervised Learning

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