Being an expert at developing and understanding ML, or Machine Learning algorithms, takes time and a lot of hard work. That’s why ML (machine learning) engineers are been seen constantly learning while at the job. If the learning stops, your professional growth stops. Many of us, especially the AI aspirants, think that watching tutorial videos on AI (artificial intelligence) modeling or ML algorithm development on YouTube…

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Mobile applications based on machine learning are reshaping and affecting many aspects of our lives. Implementing machine learning on mobile devices faces various challenges, including computational power, energy, latency, low memory, and privacy risks. In this article, we…

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In this blog, I will introduce a R package for Heterogeneous Ensemble Learning (Classification, Regression) that is fully automated. It significantly lowers the barrier for the practitioners to apply heterogeneous ensemble learning techniques in an amateur fashion to their everyday predictive problems.…

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In our previous article — 5 Challenges to be prepared for while scaling ML models, we discussed the top five challenges in productionizing scalable Machine Learning (ML) models. Our focus for this…

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Machine Learning (ML) models are designed for defined business goals. ML model productionizing refers to hosting, scaling, and running an ML Model on top of relevant datasets. ML models in production also need to be resilient and flexible for future changes and feedback. A recent study by Forrester states that improving customer experience, improving profitability & revenue growth as the key goals organizations plan to achieve specifically using ML initiatives.

Though gaining…

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Enterprise software, as well as other kinds, remains a complicated endeavor, thus necessitating the use of modern means to gauge, analyze, and adapt their performance. And one of the most popular technologies in the performance engineering market right now is machine learning. Since it has demonstrated an unparalleled ability to not only help foresee performance issues and fix them. When used in the right manner — this combination can also help performance engineering teams to steer clear of…

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Introduction:

Here’s a fun fact; An average human being (probably an adult) makes close to 30,000 conscious decisions every day. This isn’t entirely true though, in fact, I just made that number up. I could be right because if you think about it, how many decisions would you say you make on a day to day basis? Depending on who you are the above obviously varies widely and you know best. We all…

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Introduction

Artificial neural networks are based on collection of connected nodes, and are designed to identify the patterns. They are part of deep learning, in which computer systems learn to recognize patterns and perform tasks, by analyzing training examples. For example an object recognition system can be fed to thousands of labeled images of houses, cars, traffic signals, animals etc. and would…

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When creating a website, it is an essential objective of developers to make it appealing. They undergo a few systems, including drawing idea sketches, building models, and experimenting with the website before pushing it live.

These procedures don’t occur parenthetically. Developers spend many months on constructing a beautiful and responsive website. Be that as it may, the development in technologies is making things more manageable for them.

The cutting edge technologies like…

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The world has been witness to some profound changes over the past couple of decades. For example, we can shop for furniture without needing to leave our house or even send money halfway across the world with a few taps on your smartphone’s screen. However, there is one aspect of human existence that has undergone some of the most profound changes of them all — learning. Yep. Today, education is no more confined to schools, colleges, or other educational facilities. Today, students have not…

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What are the best and worst cases where machine learning algorithms can be applied? Can anyone help me in this?

It is hard to underestimate the role of E-commerce in a world where most communications happen on the web and our virtual environment is full of advertisements with attractive products and services to buy. Meanwhile, it is obvious that many criminals are trying to take advantage of it, using scams and malware to compromise users’…

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Deep Learning is a major branch of Machine Learning we have heard so much about.With or without our knowledge, deep learning is strategically influencing our day-to-day decisions.

The past few years have witnessed a…

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Such technology as AI existed for years yet experienced a significant popularity boost just a few years ago. Today, it’s far from being a futuristic thing used by the evil geniuses to conquer the planet. Instead, Artificial Intelligence became a cutting-edge tool to improve the lives of millions by assisting us with our job, studies, home duties, and even relationships. There’s no need to mention that AI start-ups are the ones to run the IT industry: $37.5 billion was spent on the start-ups…

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90% of data in existence has been generated in the last two years. On a daily basis, 7.5 sextrillion gigabytes of data are generated - around 147,000 gigabytes per person. These numbers are staggering, but it’s to be expected: the world is growing and the machine economy is growing exponentially. That's not to say that all of this data is immediately useful. Organizations can’t simply tap into these sources without massive amounts of pre-processing – but is anybody…

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Some of you are highly organized, disciplined, and keep all your belongings arranged in an ordered manner. You can easily remember the location of all these items and will be able to fetch them in a short time. But there are people who are highly unorganized and keeps all their belongings in a random manner and will have no clue on where to look for an item when they really need it. This results in a search operation on all storage spaces in the house when they want to fetch an item. There is… Continue

Machine learning (ML) is an application of Artificial Intelligence (AI) that provides the system with the ability to automatically learn and improve from experience rather than explicit programming. This is possible because today a large amount of data is available which lets machines to be trained rather than programmed. It is…

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Machine learning uses a lot of data and algorithms to predict something unexplored. Machine learning is simplifying our way of living, communicating, travel and work. Everyone uses machine learning in their daily lives. There has been a data revolution in the last few years, which has modified the way we obtain, create and communicate with the data.…

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Why do we need Learning Sprints?

Virtually every company is under pressure to transform their business in order to sustain in the future. As part of these efforts, they are hiring data scientists and engineers, data analysts, and they are making huge investments into cloud, big data technologies and AI, amongst others. Virtually all employees need to unlearn what they have assumed to be true for decades, and they have to acquire new skills. Time and money are the big…

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