NLP Leave a comment

5 Examples of Text Classification in Practice

AI is transforming nearly every industry, and text analysis is a key area of interest. That’s because there’s been an explosion in unstructured text data—nearly 80% of data at most organizations—which is quickly becoming impractical to analyze by humans alone. We’ve already talked about some best practices for building a text classifier, but how can a tool like this help your business? Let’s take a closer look at document classification and some real-world examples. What Is Document Classification? Organizations need […]

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python_tutorials
Python

How to Rename Pandas DataFrame Column in Python

Introduction Pandas is a Python library for data analysis and manipulation. Almost all operations in pandas revolve around DataFrames. A Dataframe is is an abstract representation of a two-dimensional table which can contain all sorts of data. They also enable us give all the columns names, which is why oftentimes columns are referred to as attributes or fields when using DataFrames. In this article we’ll see how we can rename an already existing DataFrame‘s columns. There are two options for […]

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python_tutorials
Python

Python: Get Size of Dictionary

Introduction In this article, we’ll take a look at how to find the size of a dictionary in Python. Dictionary size can mean its length, or space it occupies in memory. To find the number of elements stored in a dictionary we can use the len() function. To find the size of a dictionary in bytes we can use the getsizeof() function of the sys module. To count the elements of a nested dictionary, we can use a recursive function. […]

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NLP, non-autoregressive NMT

Issue #116 – Fully Non-autoregressive Neural Machine Translation

04 Feb21 Issue #116 – Fully Non-autoregressive Neural Machine Translation Author: Dr. Patrik Lambert, Senior Machine Translation Scientist @ Iconic Introduction The standard Transformer model is autoregressive (AT), which means that the prediction of each target word is based on the predictions for the previous words. The output is generated from left to right, a process which cannot be parallelised because the prediction probability of a token depends on previous tokens. In the last few years, new approaches have been […]

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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  

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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, […]

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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 […]

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python_tutorials
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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Machine Learning

Local Optimization Versus Global Optimization

Optimization refers to finding the set of inputs to an objective function that results in the maximum or minimum output from the objective function. It is common to describe optimization problems in terms of local vs. global optimization. Similarly, it is also common to describe optimization algorithms or search algorithms in terms of local vs. global search. In this tutorial, you will discover the practical differences between local and global optimization. After completing this tutorial, you will know: Local optimization […]

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python_tutorials
Python

How to Format Number as Currency String in Python

Introduction Having to manually format a number as a currency string can be a tedious process. You may have just a few lines of modifications to make, however, when we need to do a fair bit of conversions, it becomes very tedious. The first step to automating these kind of tasks will require a function. In this article, we’ll be going over a few methods you can use to format numbers as currency strings in Python. Methods for Formatting Numbers […]

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