On Thursday, I published a video on the Constant Rule, the first video in a series on Differentiation Rules. Today, we continue the series with the Power Rule, arguably the most common and most important of all the rules.
New videos are published every Monday and Thursday. The playlist for my "Calculus for ML" course is here.
More detail about my broader "ML Foundations" series and all of the associated open-source code is available in GitHub here.
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The Derivative of a Constant
This and the next several videos will provide you with clear and colorful examples of all of the most important differentiation rules. We kick these rules off with the Constant Rule.
The derivative rules are critical to machine learning as they allow us to find the derivatives of cost functions. These cost-function derivatives are concatenated into the "gradient" that we descend to allow ML models to learn.
New videos are published every Monday and Thursday. The playlist for my "Calculus for ML" course is here.
More detail about my broader "ML Foundations" series and all of the associated open-source code is available in GitHub here.
Derivative Notation
In today's YouTube video, we detail all of the most common notation for derivatives. This lays the foundation for a fun, immediately forthcoming series of videos covering all of the major differentiation rules. Enjoy!
New videos are published every Monday and Thursday. The playlist for my "Calculus for ML" course is here.
More detail about my broader "ML Foundations" series and all of the associated open-source code is available in GitHub here.
Five Keys to Success
I've recently been able to achieve markedly better results than ever before across my personal and professional lives. For Five-Minute Friday, I reflect on five keys to success that may allow achievement of many complex, long-term goals.
You can listen or watch here.
How Derivatives Arise from Limits
In today's video, we use hands-on code demos in Python to find the slopes of curves with the Delta Method. While finding these slopes, we derive together — from first principles — the most important Differential Calculus formula.
This video is part of a thematic segment of videos on Differentiation. In the forthcoming videos, we’ll cover derivative notation and a series of useful rules for differentiation.
New videos are published every Monday and Thursday. The playlist for my "Calculus for ML" course is here.
More detail about my broader "ML Foundations" series and all of the associated open-source code is available in GitHub here.
The Delta Method
In today's video, we use a Python code demo to develop a working understanding of the Delta Method, a centuries-old technique that enables us to determine the slope of a curve.
This video is the first from a thematic segment of videos on Differentiation. In Thursday's video, we'll build on what we covered today to derive — and deeply understand — the most common, most important equation in differential calculus.
New videos are published every Monday and Thursday. The playlist for my "Calculus for ML" course is here.
More detail about my broader "ML Foundations" series and all of the associated open-source code is available in GitHub here.
Derivatives and Differentiation — Segment 2 of Subject 3, "Limits & Derivative
Today marks the beginning of a new thematic segment of videos in my ML Foundations series. This segment builds on the Limits content already covered to clearly illustrate how Differentiation works and how we find Derivatives.
Through a combination of color-coded equations, paper-and-pencil exercises, and hands-on Python code demos, the videos in this segment instill a deep understanding of how differentiation allows us to find derivatives.
More specifically, the videos cover:
• The Delta Method
• The Differentiation Equation
• Differentiation Notation
• Rules that enable us to quickly calculate the derivatives of a wide range of functions, including those found throughout machine learning
New videos are published every Monday and Thursday. The playlist for my Calculus for ML course is here.
More detail about my broader ML Foundations series and all of the associated open-source code is available in GitHub here.
Exercises on Limits
Final YouTube video from my thematic segment on Limits out today! It's a handful of comprehension exercises. Starting Thursday, we'll begin releasing videos from a new Calculus segment, on derivatives and differentiation.
We release new videos from my "Calculus for Machine Learning" course on YouTube every Monday and Thursday. The playlist is here.
The Machine Learning House
In last week’s Five-Minute Friday, I discussed how, in the data science field, the learning never stops. But there’s one big counterpoint: The foundational subjects that underlie the field barely change at all, decade after decade.
These subjects — linear algebra, calculus, probability, statistics, data structures, and algorithms — build a strong foundation for your “Machine Learning House”. Today's Five-Minute Friday articulates my perspective that investing time in studying these foundational subjects will reap great dividends throughout your data science career.
You can listen or watch here.
Calculating Limits
Today's video introduces Limits, a key stepping stone toward understanding Differential Calculus. This one has lots of interactive Python code demos and paper-and-pencil exercises to ensure learning the subject is both engaging and fun.
We release new videos from my "Calculus for Machine Learning" course on YouTube every Monday and Thursday. The playlist is here.
Calculus Applications
New YouTube video out today! In this one, I provide specific examples of how calculus is applied in the real world, with an emphasis on applications to machine learning.
The YouTube playlist for my "Calculus for Machine Learning" course is here.
Calculus of the Infinitesimals
New YouTube video up! In today's we use a hands-on code demo in Python to see how approaching a curve infinitely closely enables us to determine the slope of the curve. This is key to formally understanding differential calculus.
The YouTube playlist for my "Calculus for Machine Learning" course is here.
The Method of Exhaustion
New video up on YouTube today, covering a centuries-old calculus technique called the Method of Exhaustion. The technique is still relevant today as a stepping stone to understanding how modern calculus works.
The YouTube playlist for my "Calculus for Machine Learning" course is here.
Intro to Integral Calculus
Today’s video is a quick intro to Integral Calculus, the other branch of the mathematical field alongside Differential Calculus (which was introduced in the preceding video, released on Monday).
The YouTube playlist for my "Calculus for Machine Learning" course is here.