deeplizard shows us how to add batch normalization to a convolutional neural network.

Content index:

  • 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources
  • 00:30 What is Batch Norm?
  • 04:04 Creating Two CNNs Using nn.Sequential
  • 09:42 Preparing the Training Set
  • 10:45 Injecting Networks Into Our Testing Framework
  • 14:55 Running the Tests – BatchNorm vs. NoBatchNorm
  • 16:30 Dealing with Error Caused by TensorBoard
  • 19:49 Collective Intelligence and the DEEPLIZARD HIVEMIND

deeplizard teaches us how to set up debugging for PyTorch source code in Visual Studio Code.

Content index:

  • 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources
  • 00:27 Visual Studio Code
  • 00:55 Python Debugging Extension
  • 01:30 Debugging a Python Program
  • 03:46 Manual Navigation and Control of a Program
  • 06:34 Configuring VS Code to Debug PyTorch
  • 08:44 Stepping into PyTorch Source Code
  • 10:36 Choosing the Python Environment00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources
  • 00:27 Visual Studio Code
  • 00:55 Python Debugging Extension
  • 01:30 Debugging a Python Program
  • 03:46 Manual Navigation and Control of a Program
  • 06:34 Configuring VS Code to Debug PyTorch
  • 08:44 Stepping into PyTorch Source Code
  • 10:36 Choosing the Python Environment
  • 12:30 Collective Intelligence and the DEEPLIZARD HIVEMIND

deeplizard debugs the PyTorch DataLoader to see how data is pulled from a PyTorch data set and is normalized.

We see the impact of several of the constructor parameters and see how the batch is built.

Content index:

  • 0:00 Welcome to DEEPLIZARD – Go to deeplizard.com
  • 0:45 Overview of Program Code
  • 3:12 How to Use Zen Mode
  • 3:56 Start the Debugging Process
  • 4:38 Initializing the Sampler Based on the Shuffle Parameter
  • 5:35 Debugging next(iter(dataloader))
  • 7:57 Building the Batch Using the Batch Size
  • 10:37 Get the Elements from Dataset
  • 18:43 Tensor to PIL Image
  • 20:41 Thanks for Contributing to Collective Intelligence

deeplizard teaches us how to normalize a dataset. We’ll see how dataset normalization is carried out in code, and we’ll see how normalization affects the neural network training process.

Content index:

  • 0:00 Video Intro
  • 0:52 Feature Scaling
  • 2:19 Normalization Example
  • 5:26 What Is Standardization
  • 8:13 Normalizing Color Channels
  • 9:25 Code: Normalize a Dataset
  • 19:40 Training With Normalized Data

Here’s a list of free data science courses to get up to speed while you’re locked down.

Organisations across the world are turning to data science professionals to help businesses extract insights from the vast reserves of data. This means that there is a resilient push by recruitment agencies for people skilled in data mining, programming, and statistical modelling, among others. Although the demand for talent

Demand for people with knowledge and skills in artificial intelligence (AI) and machine learning (ML) hugely outstrips the supply.

Fortunately, there are a lot of courses out there to help people up skill themselves. Many are even free.

Here’s a list of ten.

These courses are aimed at a range of different audiences – maybe you want to actually learn how to design and code AI algorithms, maybe you want to bolt together the increasing range of “DIY” AI tools and services that are available, or maybe you need to manage AI projects in your organization. Whatever your needs, you are likely to find something here that will expand your horizons.