The core of many machine learning algorithms is optimization. Optimization algorithms are used by machine learning algorithms to find a good set of model parameters given a training dataset. The most common optimization algorithm used in machine learning is stochastic gradient descent. In this tutorial, you will discover how to implement stochastic gradient descent to […]
5-Steps To Get Started and Get Good at Machine Learning I teach a 5-step process that you can use to get your start in applied machine learning. It is unconventional. The traditional way to teach machine learning is bottom-up. Start with the theory and math, then algorithm implementations, then send you off to figure out […]
The 5 Most Common Mistakes That Beginners Make And How To Avoid Them. I help beginners get started in machine learning. But I see the same mistakes in both mindset and action again and again. In this post, you will discover the 5 most common ways that I see beginners slip-up when getting started in machine […]
5 Best Practices For Operationalizing Machine Learning. Not all predictive models are at Google-scale. Sometimes you develop a small predictive model that you want to put in your software. I recently received this reader question: Actually, there is a part that is missing in my knowledge about machine learning. All tutorials give you the steps up […]
From Developer to Machine Learning Practitioner in 14 Days Python is one of the fastest-growing platforms for applied machine learning. In this mini-course, you will discover how you can get started, build accurate models and confidently complete predictive modeling machine learning projects using Python in 14 days. This is a big and important post. You […]
Getting started in deep learning is a struggle. It’s a struggle because deep learning is taught by academics, for academics. If you’re a developer (or practitioner), you’re different. You want results. The way practitioners learn new technologies is by developing prototypes that deliver value quickly. This is a top-down approach to learning, but it is not the way […]
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XGBoost is an algorithm that has recently been dominating applied machine learning and Kaggle competitions for structured or tabular data. XGBoost is an implementation of gradient boosted decision trees designed for speed and performance. In this post you will discover XGBoost and get a gentle introduction to what is, where it came from and how […]
Sentiment analysis is a natural language processing problem where text is understood, and the underlying intent is predicted. In this post, you will discover how you can predict the sentiment of movie reviews as either positive or negative in Python using the Keras deep learning library. After reading this post, you will know: About the […]
Machine Learning Mastery With Weka Discover How To Build Predictive Models In Minutes Without The Code, Without The Math and Without the Confusion Getting Started in Applied Machine Learning is Hard …it’s hard for more reasons than you even know When you start out in applied machine learning, there is so much to learn. For example: […]
