Machine Learning

Linear Algebra for Deep Learning

Last Updated on August 9, 2019 Linear algebra is a field of applied mathematics that is a prerequisite to reading and understanding the formal description of deep learning methods, such as in papers and textbooks. Generally, an understanding of linear algebra (or parts thereof) is presented as a prerequisite for machine learning. Although important, this area of mathematics is seldom covered by computer science or software engineering degree programs. In their seminal textbook on deep learning, Ian Goodfellow and others […]

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Machine Learning

Computational Linear Algebra for Coders Review

Last Updated on August 9, 2019 Numerical linear algebra is concerned with the practical implications of implementing and executing matrix operations in computers with real data. It is an area that requires some previous experience of linear algebra and is focused on both the performance and precision of the operations. The company fast.ai released a free course titled “Computational Linear Algebra” on the topic of numerical linear algebra that includes Python notebooks and video lectures recorded at the University of […]

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Machine Learning

Linear Algebra for Machine Learning (7-Day Mini-Course)

Last Updated on August 9, 2019 Linear Algebra for Machine Learning Crash Course. Get on top of the linear algebra used in machine learning in 7 Days. Linear algebra is a field of mathematics that is universally agreed to be a prerequisite for a deeper understanding of machine learning. Although linear algebra is a large field with many esoteric theories and findings, the nuts and bolts tools and notations taken from the field are required for machine learning practitioners. With […]

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Machine Learning

Basics of Mathematical Notation for Machine Learning

Last Updated on May 7, 2020 You cannot avoid mathematical notation when reading the descriptions of machine learning methods. Often, all it takes is one term or one fragment of notation in an equation to completely derail your understanding of the entire procedure. This can be extremely frustrating, especially for machine learning beginners coming from the world of development. You can make great progress if you know a few basic areas of mathematical notation and some tricks for working through […]

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Machine Learning

Why Machine Learning Does Not Have to Be So Hard

Last Updated on July 13, 2019 Technical topics like mathematics, physics, and even computer science are taught using a bottom-up approach. This approach involves laying out the topics in an area of study in a logical way with a natural progression in complexity and capability. The problem is, humans are not robots executing a learning program. We require motivation, excitement, and most importantly, a connection of the topic to tangible results. Useful skills we use every day like reading, driving, […]

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Machine Learning

Comparing 13 Algorithms on 165 Datasets (hint: use Gradient Boosting)

Last Updated on August 21, 2019 Which machine learning algorithm should you use? It is a central question in applied machine learning. In a recent paper by Randal Olson and others, they attempt to answer it and give you a guide for algorithms and parameters to try on your problem first, before spot checking a broader suite of algorithms. In this post, you will discover a study and findings from evaluating many machine learning algorithms across a large number of […]

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Machine Learning

How to Think About Machine Learning

Last Updated on August 15, 2019 Machine learning is a large and interdisciplinary field of study. You can achieve impressive results with machine learning and find solutions to very challenging problems. But this is only a small corner of the broader field of machine learning often called predictive modeling or predictive analytics. In this post, you will discover how to change the way you think about machine learning in order to best serve you as a machine learning practitioner. After […]

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Machine Learning

So, You are Working on a Machine Learning Problem…

Last Updated on January 9, 2019 So, you’re working on a machine learning problem. I want to really nail down where you’re at right now. Let me make some guesses… So, You are Working on a Machine Learning Problem…Photo by David Mulder, some rights reserved. 1) You Have a Problem So you have a problem that you need to solve. Maybe it’s your problem, an idea you have, a question, or something you want to address. Or maybe it is […]

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Machine Learning

How to Make Predictions with scikit-learn

Last Updated on January 10, 2020 How to predict classification or regression outcomeswith scikit-learn models in Python. Once you choose and fit a final machine learning model in scikit-learn, you can use it to make predictions on new data instances. There is some confusion amongst beginners about how exactly to do this. I often see questions such as: How do I make predictions with my model in scikit-learn? In this tutorial, you will discover exactly how you can make classification […]

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Machine Learning

How to Make Predictions with Keras

Last Updated on August 27, 2020 Once you choose and fit a final deep learning model in Keras, you can use it to make predictions on new data instances. There is some confusion amongst beginners about how exactly to do this. I often see questions such as: How do I make predictions with my model in Keras? In this tutorial, you will discover exactly how you can make classification and regression predictions with a finalized deep learning model with the […]

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