February 3, 2021 Computer Vision Leave a comment

Microsoft Vision Model ResNet-50 combines web-scale data and multi-task learning to achieve state of the art

Microsoft Vision Model ResNet-50 is a state-of-the-art pretrained ResNet-50 model, measured above by the mean average score across seven popular computer vision benchmarks. Pretrained vision models accelerate deep learning research and bring down the cost of performing computer vision tasks in production. By pretraining one large vision model to learn general visual representation of images, then transferring the learning across multiple downstream tasks, a team achieves competitive performance at a fraction of the cost when compared to collecting new

February 3, 2021 Machine Learning

Difference Between Backpropagation and Stochastic Gradient Descent

Last Updated on February 1, 2021 There is a lot of confusion for beginners around what algorithm is used to train deep learning neural network models. It is common to hear neural networks learn using the “back-propagation of error” algorithm or “stochastic gradient descent.” Sometimes, either of these algorithms is used as a shorthand for how a neural net is fit on a training dataset, although in many cases, there is a deep confusion as to what these algorithms are, […]

February 3, 2021 Machine Learning

Weight Initialization for Deep Learning Neural Networks

Weight initialization is an important design choice when developing deep learning neural network models. Historically, weight initialization involved using small random numbers, although over the last decade, more specific heuristics have been developed that use information, such as the type of activation function that is being used and the number of inputs to the node. These more tailored heuristics can result in more effective training of neural network models using the stochastic gradient descent optimization algorithm. In this tutorial, you […]

February 1, 2021 Python

Python: How to Handle Missing Data in Pandas DataFrame

Introduction Pandas is a Python library for data analysis and manipulation. Almost all operations in pandas revolve around DataFrames, an abstract data structure tailor-made for handling a metric ton of data. In the aforementioned metric ton of data, some of it is bound to be missing for various reasons. Resulting in a missing (null/None/Nan) value in our DataFrame. Which is why, in this article, we’ll be discussing how to handle missing data in a Pandas DataFrame. Data Inspection Real-world datasets […]

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