decision tree


50 Frequently Asked Machine Learning Interview Questions and Answers

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At present, machine learning, artificial intelligence, and data science are the most booming factor to bring the next revolution in this industrial and technology-driven world. Therefore, there are a significant number of opportunities that are waiting for fresh graduate data scientists and machine learning developers to apply their specific knowledge in a particular domain. However, it's not that easy as you are thinking. The interview procedure that you will have to go through will definitely be very challenging, and you will have hard competitors. Moreover, your skill will be tested in different ways, i.e., technical and programming skills, problem-solving skills, and your ability to apply machine learning techniques efficiently and effectively, and your overall knowledge about machine learning. To help you with your upcoming interview, in this post, we have listed frequently asked machine learning interview questions. Traditionally, to recruit a machine learning developer, several types of machine learning interview questions are asked. Firstly, some basic machine learning questions are asked. Then, machine learning algorithms, their comparisons, benefits, and drawbacks are asked. Finally, the problem-solving skill using these algorithms and techniques are examined.


A Gentle Introduction to Information Entropy

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Information theory is a subfield of mathematics concerned with transmitting data across a noisy channel. A cornerstone of information theory is the idea of quantifying how much information there is in a message. More generally, this can be used to quantify the information in an event and a random variable, called entropy, and is calculated using probability. Calculating information and entropy is a useful tool in machine learning and is used as the basis for techniques such as feature selection, building decision trees, and, more generally, fitting classification models. As such, a machine learning practitioner requires a strong understanding and intuition for information and entropy.


The best of both worlds: R meets Python via reticulate

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As far as rivalries go, R vs Python can almost reach the levels of the glory days of Barca vs Madrid, Stones vs Beatles, or Sega vs Nintendo. Just dare to venture onto Twitter asking which language is best for data science to witness two tightly entrenched camps. Or at least that's what seemingly hundreds of Medium articles would like you believe. In reality, beyond some good-natured and occasionally entertaining joshing, the whole debate is rather silly. Because the question itself is wrong.


How I scored in the top 1% of Kaggle's Titanic Machine Learning Challenge

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You don't need to reinvent the wheel, you need to know how to use the wheel to make your car better. The Titanic challenge hosted by Kaggle is a competition in which the goal is to predict the survival or the death of a given passenger based on a set of variables describing him such as his age, his sex, or his passenger class on the boat. I have been playing with the Titanic dataset for a while. As I'm writing this post, I am ranked 113th out of 11002 participants. You must be wondering how did I manage to achieve this.


How I scored in the top 1% of Kaggle's Titanic Machine Learning Challenge

#artificialintelligence

You don't need to reinvent the wheel, you need to know how to use the wheel to make your car better. The Titanic challenge hosted by Kaggle is a competition in which the goal is to predict the survival or the death of a given passenger based on a set of variables describing him such as his age, his sex, or his passenger class on the boat. I have been playing with the Titanic dataset for a while. As I'm writing this post, I am ranked 113th out of 11002 participants. You must be wondering how did I manage to achieve this.


Using Artificial Intelligence in your business: Key questions to answer before deploying WRAL TechWire

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Editor's note: This is the latest in an exclusive UpTech series about Artificial Intelligence, Machine Learning and much more as part of a partnership between YourLocalStudio.com and WRAL TechWire. Previous posts can be found by searching "Uptech" at WRAL TechWire.com. Interviews are conducted by Alexander Ferguson, CEO of YourLocalStudio.com. In this deep dive video, we hear from Dr. Chris Hazard, a unique figure in the world of artificial intelligence who draws from experience in software development, psychology, physics, economics, hypnosis, robotics, and privacy law. He has worked in and been published in a variety of fields from wireless network infrastructure as a software architect at Motorola, to psychology as part of a post-doc at NCSU, to hypnosis with the National Guild of Hypnotists, to robotics at Kiva Systems, to privacy law working with the Future of Privacy Forum.]


Why the 'why way' is the right way to restoring trust in AI - KDnuggets

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"Why? - Because I am your mother, that's why." - My mom/your mom/everyone's mom. Artificial Intelligence is growing in sophistication, autonomy, and market reach offering transformational opportunities for businesses and their customers. AI relies on the collection and smart processing of personal information to function. However, the privacy scandals of social media and recent breaches of consumer data have eroded consumer confidence: not only around data usage but the implications of its omnipotence. We live in an age of maximum customer empowerment and, as a result, maximum business anxiety.


microsoft/LightGBM

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LightGBM is a gradient boosting framework that uses tree based learning algorithms. For further details, please refer to Features. Benefitting from these advantages, LightGBM is being widely-used in many winning solutions of machine learning competitions. Comparison experiments on public datasets show that LightGBM can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. What's more, parallel experiments show that LightGBM can achieve a linear speed-up by using multiple machines for training in specific settings.


Creativity and AI: The Next Step

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In 1997 IBM's Deep Blue famously defeated chess Grand Master Garry Kasparov after a titanic battle. It had actually lost to him the previous year, though he conceded that it seemed to possess "a weird kind of intelligence." To play Kasparov, Deep Blue had been pre-programmed with intricate software, including an extensive playbook with moves for openings, middle game and endgame. Twenty years later, in 2017, Google unleashed AlphaGo Zero which, unlike Deep Blue, was entirely self-taught. It was given only the basic rules of the far more difficult game of Go, without any sample games to study, and worked out all its strategies from scratch by playing millions of times against itself.


Robots.net 25 Machine Learning Interview Questions You Must Know

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It seems like everyone is looking to start a career in artificial intelligence and machine learning nowadays. That's no surprise when you take into account the high salaries, a multitude of available job offers, and an opportunity to work with some of the hottest companies around. You'll need to familiarize youself with popular machine learning interview questions. At the same time, the fact that a lot of people are currently interested in machine learning as a career means that there are fewer jobs to go around. If you want to stand out from the crowd, you have to ace that machine learning interview.