An Easy Introduction To AI And Deep Learning

8.5 Hours
You save 85% -

62 Lessons (8.5h)

  • You, This Course and Us
    You, This Course and Us2:38
    Source Code and PDFs
    Datasets for all Labs
  • Installation
    Install TensorFlow6:24
    Install Jupyter Notebook4:38
    Running on the GCP vs. Running on your local machine
    Lab: Setting Up A GCP Account6:59
    Lab: Using The Cloud Shell6:01
    Datalab ~ Jupyter3:00
    Lab: Creating And Working On A Datalab Instance10:29
  • TensorFlow and Machine Learning
    Introducing Machine Learning8:04
    Representation Learning10:27
    Neural Networks Introduced7:35
    Introducing TensorFlow7:16
    Running on the GCP vs. Running on your local machine
    Lab: Simple Math Operations8:46
    Computation Graph10:17
    Lab: Tensors5:03
    Linear Regression Intro9:57
    Placeholders and Variables8:44
    Lab: Placeholders6:36
    Lab: Variables7:49
    Lab: Linear Regression with Made-up Data4:52
    Quiz 1: TensorFlow Basics
  • Working with Images
    Image Processing8:05
    Images As Tensors8:16
    Lab: Reading and Working with Images8:05
    Lab: Image Transformations6:37
    Quiz 2: Images
  • K-Nearest-Neighbors with TensorFlow
    Introducing MNIST4:13
    K-Nearest Neigbors as Unsupervised Learning7:42
    One-hot Notation and L1 Distance7:31
    Steps in the K-Nearest-Neighbors Implementation9:32
    Lab: K-Nearest-Neighbors14:14
    Quiz 3: MNIST with K-Nearest Neighbors
  • Linear Regression with a Single Neuron
    Learning Algorithm10:58
    Individual Neuron9:52
    Learning Regression7:51
    Learning XOR10:26
    XOR Trained11:11
  • Linear Regression in TensorFlow
    Lab: Access Data from Yahoo Finance2:49
    Non TensorFlow Regression8:05
    Lab: Linear Regression - Setting Up a Baseline11:18
    Gradient Descent9:56
    Lab: Linear Regression14:42
    Lab: Multiple Regression in TensorFlow9:15
    Quiz 4: Linear Regression
  • Logistic Regression in TensorFlow
    Logistic Regression Introduced10:16
    Linear Classification5:25
    Lab: Logistic Regression - Setting Up a Baseline7:33
    Lab: Logistic Regression16:56
    Quiz 5: Logistic Regression
  • The Estimator API
    Lab: Linear Regression using Estimators7:49
    Lab: Logistic Regression using Estimators4:54
    Quiz 6: Estimators
  • Neural Networks and Deep Learning
    Traditional Machine Learning6:24
    Deep Learning9:23
    Operation of a Single Neuron8:17
    The Activation Function10:41
    Training a Neural Network: Back Propagation6:40
    Lab: Automobile Price Prediction - Exploring the Dataset11:13
    Lab: Automobile Price Prediction - Using TensorFlow for Prediction14:35
    Vanishing and Exploding Gradients12:10
    The Bias-Variance Trade-off8:26
    Preventing Overfitting7:36
    Lab: Iris Flower Classification12:08
    Quiz 7: Neural Networks and Deep Learning

Get Your Feet Wet with the Backbone to Siri, Self-Driving Cars & More



Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertise at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.


Deep learning isn't just about helping computers learn from data—it's about helping those machines determine what's important in those datasets. This is what allows for Tesla's Model S to drive on its own and for Siri to determine where the best brunch spots are. Using the machine learning workhorse that is TensorFlow, this course will show you how to build deep learning models and explore advanced AI capabilities with neural networks.

  • Access 62 lectures & 8.5 hours of content 24/7
  • Understand the anatomy of a TensorFlow program & basic constructs such as graphs, tensors, and constants
  • Create regression models w/ TensorFlow
  • Learn how to streamline building & evaluating models w/ TensorFlow's estimator API
  • Use deep neural networks to build classification & regression models


Important Details

  • Length of time users can access this course: lifetime
  • Access options: web
  • Certification of completion not included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: intermediate


  • Unredeemed licenses can be returned for store credit within 30 days of purchase. Once your license is redeemed, all sales are final.
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