The Complete Python Course for Machine Learning Engineers

@machinelearnbot

"I took a few of your courses and you are an amazing teacher. Your courses have brought me up to speed on how to create databases and how to interact and handle Data Engineers and Data Scientists. I will be forever grateful." "By taking this course my perception has changed and now data science for me is more about data wrangling. Welcome to The Complete Course for Machine Learning Engineers.


SciKit-Learn in Python for Machine Learning Engineers

@machinelearnbot

This is the fourth course in the series designed to prepare you for a real world job in the machine learning space. I'd highly recommend you take the courses serially. People love building models and many think that machine learning engineers sit around and build models all day. Take the courses in order to understand what machine learning engineers really do. In this course we are going to learn SciKit-Learn using a lab integrated approach.


SciPy Cheat Sheet: Linear Algebra in Python

#artificialintelligence

By now, you will have already learned that NumPy, one of the fundamental packages for scientific computing, forms at least for a part the fundament of other important packages that you might use used for data manipulation and machine learning with Python. One of those packages is SciPy, another one of the core packages for scientific computing in Python that provides mathematical algorithms and convenience functions built on the NumPy extension of Python. You might now wonder why this library might come in handy for data science. Well, SciPy has many modules that will help you to understand some of the basic components that you need to master when you're learning data science, namely, math, stats and machine learning. You can find out what other things you need to tackle to learn data science here.


Feature Engineering with Kaggle Tutorial

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In the two previous Kaggle tutorials, you learned all about how to get your data in a form to build your first machine learning model, using Exploratory Data Analysis and baseline machine learning models. Next, you successfully managed to build your first machine learning model, a decision tree classifier. You submitted all these models to Kaggle and interpreted their accuracy.


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.