book updates

book-content/02-learning-path-opening-thoughts.Rmd

@@ -2,6 +2,9 @@
 
 # Opening Thoughts {#learning-path-opening-thoughts}
 
+![](images/1.1.gif)
+[source](https://dilbert.com/strip/2017-09-07)
+
 ## The Future
 
 Every day new technology is being released that is poised to turn the world of corporate finance upside down. The type of tech that changes not just how you get your job done, but what types of work you do day to day. Machines are getting better and better on more of the mundane tasks of our every day lives, and soon they will encroach on things we deem as hard or creative. This might seem like a scary future, where jobs are at stake and there is a zero sum game with machines taking all of the chips at the end of the day. The good news is the exact opposite will happen!

book-content/03-non-technical-ml-learning.Rmd

@@ -2,6 +2,9 @@
 
 ## Intro to AI
 
+![](images/2.1.gif)
+[source](https://dilbert.com/strip/2018-11-24)
+
 ### Introduction
 
 ### Overview of AI and ML
@@ -48,6 +51,9 @@
 
 ## Book List
 
+![](images/2.2.gif)
+[source](https://dilbert.com/strip/1989-05-28)
+
 ### General AI Books
 
 * [Reprogamming the American Dream](https://www.amazon.com/Reprogramming-American-Dream-America-Valley-Making-ebook/dp/B07V1W37XK/ref=sr_1_1?crid=2OAPWAOX7DY27&dchild=1&keywords=reprogramming+the+american+dream&qid=1632757570&s=books&sprefix=reprogammning+the+%2Caps%2C258&sr=1-1)

book-content/04-technical-ml-learning.Rmd

@@ -2,6 +2,9 @@
 
 ## Introduction
 
+![](images/3.1.jpg_large)
+[source](https://pbs.twimg.com/media/CnTztGXWAAAWDXO.jpg:large)
+
 ### Opening Thoughts
 * There are many ways to learn technical material. Paid courses, YouTube videos, blog posts, and books are all equally effective based on your learning style. The content in the following sections tries to have a healthy balance of all content types. 
 * By default, all of the recommended learning content is free. There are additional resources mentioned where you might have to pay for. These serve as additional avenues to strengthen the concepts and techniques learned in the initial free content. 
@@ -17,6 +20,9 @@
 
 ## Installing Software
 
+![](images/3.2.gif)
+[source](https://dilbert.com/strip/2018-08-03)
+
 ### Python
 * [Coding Tools for Python Development](https://docs.microsoft.com/en-us/learn/modules/install-code-tools-python-nasa/)
 * [VSCode Python Setup](https://www.youtube.com/playlist?list=PLo32uKohmrXt7VB91DLB-hMcDcWswE53Y)
@@ -29,6 +35,9 @@
 
 ## Data Analysis and Manipulation
 
+![](images/3.3.gif)
+[source](https://dilbert.com/strip/2017-07-10)
+
 ### Python
 * Pick one of the following
     + [Option 1 - Free Code Camp](https://www.freecodecamp.org/learn/data-analysis-with-python/)
@@ -64,6 +73,9 @@
 
 ## Version Control
 
+![](images/3.4.gif)
+[source](https://dilbert.com/strip/2000-09-21)
+
 ### High Level Overview
 
 * [Git and GitHub for Beginners](https://www.youtube.com/watch?v=RGOj5yH7evk&t=491s)
@@ -83,6 +95,9 @@
 
 ## Machine Learning Basics
 
+![](images/3.5.gif)
+[source](https://dilbert.com/strip/2014-07-04)
+
 ### High Level Topics
 
 * [Three Things to do when Starting Out in Data Science](https://www.youtube.com/watch?v=ilUbD7EoQnk)
@@ -125,6 +140,9 @@
 
 ## Regression
 
+![](images/3.6.gif)
+[source](https://dilbert.com/strip/2016-06-21)
+
 ### High Level Topics
 
 * [Making Friends with Regression](https://www.youtube.com/watch?v=WNvOtwP_yf4)
@@ -167,6 +185,9 @@
 
 ## Time Series
 
+![](images/3.7.gif)
+[source](https://dilbert.com/strip/2001-12-29)
+
 ### High Level Topics
 
 * [Time Series Forecasting with Machine Learning](https://www.youtube.com/watch?v=_ZQ-lQrK9Rg)
@@ -203,6 +224,9 @@
 
 ## Classification
 
+![](images/3.8.gif)
+[source](https://dilbert.com/strip/2018-08-02)
+
 ### High Level Topics
 
 * [Classification in Machine Learning](https://www.youtube.com/watch?v=pXdum128xww) (skip tutorial at end)
@@ -250,6 +274,9 @@
 
 ## Unsupervised Learning
 
+![](images/3.9.gif)
+[source](https://dilbert.com/strip/2018-01-06)
+
 ### Python
 
 * [Train and Evaluate Clustering Models](https://docs.microsoft.com/en-us/learn/modules/train-evaluate-cluster-models/)
@@ -270,6 +297,9 @@
 
 ## Natural Language Processing
 
+![](images/3.10.gif)
+[source](https://dilbert.com/strip/2017-07-13)
+
 ### Python
 
 * [Natural Language Processing: Kaggle](https://www.kaggle.com/learn/natural-language-processing)
@@ -291,6 +321,9 @@
 
 ## Deep Learning
 
+![](images/3.11.gif)
+[source](https://dilbert.com/strip/2021-03-12)
+
 ### High Level Topics
 
 * [Deep Learning Crash Course](https://www.youtube.com/watch?v=VyWAvY2CF9c)
@@ -318,6 +351,9 @@
 
 ## Model Interpretability
 
+![](images/3.12.gif)
+[source](https://dilbert.com/strip/1998-12-10)
+
 ### High Level Topics
 
 * [Interpretable Machine Learning](https://christophm.github.io/interpretable-ml-book/)
@@ -335,6 +371,9 @@
 
 ## AI Ethics and Fairness
 
+![](images/3.13.gif)
+[source](https://dilbert.com/strip/2015-02-10)
+
 ### High Level Topics
 
 * [Intro to AI Ethics: Kaggle](https://www.kaggle.com/learn/intro-to-ai-ethics)
@@ -348,6 +387,9 @@
 
 ## Web Apps
 
+![](images/3.14.jpg)
+[source](https://dilbert.com/strip/2016-03-06)
+
 ### Python
 
 * [Python Web Applications with Flask](https://www.youtube.com/watch?v=Qr4QMBUPxWo)
@@ -364,4 +406,10 @@
 
 ## Production on Azure
 
-## Life as a Data Scientist
+![](images/3.15.gif)
+[source](https://dilbert.com/strip/2014-01-17)
+
+## Life as a Data Scientist
+
+![](images/3.16.gif)
+[source](https://dilbert.com/strip/2018-04-03)