Advanced Deep Learning With Neural Networks

3.5 Hours
You save 85% -

28 Lessons (3.5h)

  • You, This Course and Us
    You, This Course and Us2:38
    Source Code and PDFs
    Datasets for all Labs
  • Convolutional Neural Networks (CNNs)
    Mimicking the Visual Cortex5:07
    Choice of Kernel Functions4:47
    Zero Padding and Stride Size5:47
    CNNs vs DNNs7:15
    Feature Maps9:29
    Lab: Classification of Street View House Numbers - Exploring the Dataset10:37
    Basic Architecture of a CNN7:07
    Lab: Classification of Street View House Numbers - Building the Model12:52
    Lab: Classification of Street View House Numbers - Running the Model7:35
    Lab: Building a CNN Using the Estimator API12:19
    Quiz 9: Convolutional Neural Networks (CNNs)
  • Classifiers and Classification
    Classification as an ML Problem7:49
    Confusion Matrix: Accuracy, Precision and Recall12:38
    Decision Thresholds and The Precision-Recall Trade-off10:44
    F1 Scores and The ROC Curve7:45
    Quiz 8: Classification
  • Recurrent Neural Networks (RNNs)
    Learning From the Past8:31
    Unrolling an RNN Cell Through Time6:54
    Training an RNN - Back Propagation Through Time8:23
    Lab: RNNs for Image Classifcation14:21
    Vanishing and Exploding Gradients in an RNN7:05
    Long Memory Neurons vs Truncated BPTT6:03
    The Long/Short Term Memory Cell6:28
    A Sequence of Words6:35
    Text in Numeric Form15:08
    Lab: Sentiment Analysis on Rotten Tomatoes Reviews - Exploring the Dataset10:35
    Lab: Sentiment Analysis on Rotten Tomatoes Reviews - Building, Running the Model11:20
    Quiz 10: Recurrent Neural Networks (RNNs)

Add TensorFlow to Your Deep Learning Toolbox



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.


Work as a deep learning developer would be infinitely harder without TensorFlow. Created by Google in 2015, this open-source software library makes it easier for developers to design, build, and train deep learning models. Using TensorFlow, this course will guide you through Convolutional Neural Networks and Recurrent Neural Networks, cutting-edge tools in image recognition, language modeling, and working with high-frequency data.

  • Access 28 lectures & 3.5 hours of content 24/7
  • Use TensorFlow to work w/ convolutional & recurrent neural networks
  • Learn how neural networks contribute to image recognition & language modeling
  • Explore real-world deep learning examples via lab lessons


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: all levels


  • 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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