21 Machine Learning Interview Questions and Answers

If you want to land a job in data science, you’ll need to pass a rigorous and competitive interview process. In fact, most top companies will have at least 3 rounds of interviews. During the process, you’ll be tested for a variety of skills, including: Your technical and programming skills Your ability to structure solutions…

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8 Fun Machine Learning Projects for Beginners

In this guide, we’ll be walking through 8 fun machine learning projects for beginners. Projects are some of the best investments of your time. You’ll enjoy learning, stay motivated, and make faster progress. You see, no amount of theory can replace hands-on practice. Textbooks and lessons can lull you into a false belief of mastery because…

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Overfitting in Machine Learning: What It Is and How to Prevent It

Did you know that there’s one mistake… …that thousands of data science beginners unknowingly commit? And that this mistake can single-handedly ruin your machine learning model? No, that’s not an exaggeration. We’re talking about one of the trickiest obstacles in applied machine learning: overfitting. But don’t worry: In this guide, we’ll walk you through exactly…

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Datasets for Data Science and Machine Learning

These days, we have the opposite problem we had 5-10 years ago… Back then, it was actually difficult to find datasets for data science and machine learning projects. Since then, we’ve been flooded with lists and lists of datasets. Today, the problem is not finding datasets, but rather sifting through them to keep the relevant…

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How to Learn Python for Data Science in 2017 (Updated)

In this guide, we’ll cover how to learn Python for data science, including our favorite curriculum for self-study. You see, data science is about problem solving, exploration, and extracting valuable information from data. To do so effectively, you’ll need to wrangle datasets, train machine learning models, visualize results, and much more. Enter Python. This is the…

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Best Practices for Feature Engineering

Feature engineering, the process creating new input features for machine learning, is one of the most effective ways to improve predictive models. Coming up with features is difficult, time-consuming, requires expert knowledge. “Applied machine learning” is basically feature engineering. ~ Andrew Ng Through feature engineering, you can isolate key information, highlight patterns, and bring in…

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The Beginner’s Guide to Kaggle

Kaggle, a popular platform for data science competitions, can be intimidating for beginners to get into. After all, some of the listed competitions have over $1,000,000 prize pools and hundreds of competitors. Top teams boast decades of combined experience, tackling ambitious problems such as improving airport security or analyzing satellite data. It’s no surprise that some beginners hesitate to…

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How to Handle Imbalanced Classes in Machine Learning

Imbalanced classes put “accuracy” out of business. This is a surprisingly common problem in machine learning (specifically in classification), occurring in datasets with a disproportionate ratio of observations in each class. Standard accuracy no longer reliably measures performance, which makes model training much trickier. Imbalanced classes appear in many domains, including: Fraud detection Spam filtering Disease screening SaaS subscription churn Advertising click-throughs In this…

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9 Mistakes to Avoid When Starting Your Career in Data Science

If you wish to begin a career in data science, you can save yourself days, weeks, or even months of frustration by avoiding these 9 costly beginner mistakes. If you’re not careful, these mistakes will eat away at your most valuable resources: your time, energy, and motivation. We’ve broken them into three categories: Mistakes while…

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WTF is the Bias-Variance Tradeoff? (Infographic)

Overheard after class: “doesn’t the Bias-Variance Tradeoff sound like the name of a treaty from a history documentary?” Ok, that’s fair… but it’s also one of the most important concepts to understand for supervised machine learning and predictive modeling. Unfortunately, because it’s often taught through dense math formulas, it’s earned a tough reputation. But as you’ll…

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