Updated slides

Author: IntegerMan

part0_intro.ipynb

@@ -14,6 +14,8 @@
    "source": [
     "## Who am I?\n",
     "\n",
+    "![IntroSlide](screens/SlideIntro.png)\n",
+    "\n",
     "After 20+ years of software engineering and engineering management I now teach professionally and do many things including: \n",
     "\n",
     "- Teaching Software Development @ [Tech Elevator](https://TechElevator.com) in Columbus, OH\n",
@@ -38,7 +40,9 @@
    "source": [
     "## What's this talk about?\n",
     "\n",
-    "**Machine Learning in Azure using Python**. Seems kinda obvious.\n",
+    "Unsurprisingly, we're talking about **Machine Learning in Azure using Python**\n",
+    "\n",
+    "![Talk Goals](screens/SlideGoals.png)\n",
     "\n",
     "Some specific areas we'll cover:\n",
     "\n",
@@ -47,6 +51,10 @@
     "- Why would I even want to use Azure for this?\n",
     "- What does Python code look like for working with Azure?\n",
     "\n",
+    "**Note:** Full source code for this talk is available at [https://github.com/IntegerMan/AutoMLwithPythonAndAzure](https://github.com/IntegerMan/AutoMLwithPythonAndAzure)\n",
+    "\n",
+    "---\n",
+    "\n",
     "For the bulk of this talk, we'll explore a **regression experiment** on hockey penalty prediction from data exploration to automated machine learning to model deployment and consumption.\n",
     "\n",
     "We'll also look briefly at a prior **classification experiment** on Die Hard to see the types of metrics available when looking at classification experiments."
@@ -58,7 +66,7 @@
    "source": [
     "## Touring Azure Machine Learning Studio\n",
     "\n",
-    "Let's take a look at Azure Machine Learning Studio to see what the Azure ML SDK allows us to automate.\n",
+    "Let's take a look at [Azure Machine Learning Studio](https://portal.azure.com) to see what the Azure ML SDK allows us to automate.\n",
     "\n",
     "![](screens/AutoMLModelPerformance.png)"
    ]

part2_automl_nhl_regression.ipynb

@@ -1,5 +1,31 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Other Topics\n",
+    "\n",
+    "### Hyperdrive\n",
+    "Hyperdrive lets you automatically tune hyperparameters for a script to maximize or minimize a target metric.\n",
+    "![Hyperdrive Code](screens/HyperdriveCode.png)\n",
+    "\n",
+    "A Hyperdrive run is like AutoML, but targeted at a specific piece of code you provide and seeks to find the best combination of hyperparameters.\n",
+    "![Hyperdrive Run](screens/HyperdriveRun.png)\n",
+    "\n",
+    "### Azure Cognitive Services\n",
+    "\n",
+    "Azure Cognitive Services lets you work with pay-per-use APIs that expose pre-trained customizable image, text, and speech machine learning algorithms.\n",
+    "\n",
+    "![Azure Cognitive Services](screens/AzureCognitiveServices.png)\n",
+    "\n",
+    "### Azure Synapse Analytics\n",
+    "\n",
+    "Azure Synapse Analytics is a data ingestion and transformation solution that lets you automate feeding pre-processed data into the model training or prediction generation processes for Azure Machine Learning Studio.\n",
+    "\n",
+    "![Azure Synapse Analytics](screens/AzureSynapse.png)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -25,6 +51,17 @@
     "%pip install plotly         # Used for data visualization"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### View this Code\n",
+    "\n",
+    "This is a public GitHub repository, so you can find the code and tailor it to your own experiments on your own Azure accounts.\n",
+    "\n",
+    "Visit [https://github.com/IntegerMan/AutoMLwithPythonAndAzure](https://github.com/IntegerMan/AutoMLwithPythonAndAzure) for the full source code."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -39,12 +76,25 @@
     "- Other services perpetually free"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Kaggle.com\n",
+    "\n",
+    "[Kaggle](https://kaggle.com/datasets) is a very good way of getting free data sources for data science experiments.\n",
+    "\n",
+    "![Kaggle](screens/Kaggle.png)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Learning More\n",
     "\n",
+    "![MattEland.dev](screens/MattElandDev.png)\n",
+    "\n",
     "### My Content\n",
     "\n",
     "- [AccessibleAI.dev](https://AccessibleAI.dev) - Data Science Blog\n",