Machine Learning

A Gentle Introduction to Stochastic Optimization Algorithms

Stochastic optimization refers to the use of randomness in the objective function or in the optimization algorithm. Challenging optimization algorithms, such as high-dimensional nonlinear objective problems, may contain multiple local optima in which deterministic optimization algorithms may get stuck. Stochastic optimization algorithms provide an alternative approach that permits less optimal local decisions to be made within the search procedure that may increase the probability of the procedure locating the global optima of the objective function. In this tutorial, you will […]

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Neural Machine Translation (NMT), NMT Leave a comment

Machine Translation Weekly 68: Pre-editing of MT inputs

Today, I am going to comment on a paper that systematically explores something that probably many MT users do this is pre-editing (editing the source sentence) to get a better output of an MT that is treated as a black box. The title of the paper is Understanding Pre-Editing for Black-Box Neural Machine Translation by authors from Nagoya University and NICT in Japan and will appear at this year’s EACL. Pre-editing is something I often do when I use automatic […]

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python_tutorials
Python

Python: How to Add Key to a Dictionary

Introduction A dictionary in Python is a collection of items that store data as key-value pairs. We can access and manipulate dictionary items based on their key. Dictionaries are mutable and allow us to add new items to them. The quickest way to add a single item to a dictionary is by using referencing a dictionary’s index with a new key and assigning a value. For example, we add a new key-value pair like this: snacks[‘chocolate’] = 5 Python allows […]

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python_tutorials
Python

Python: How to Remove a Key from a Dictionary

Introduction In this article, we’ll take a look at how to remove keys from Python dictionaries. This can be done with the pop() function, the del keyword, and with dict comprehensions. Remove a Key Using pop(key,d) The pop(key, d) function removes a key from a dictionary and returns its value. It takes two arguments, the key is removed and the optional value to return if the key isn’t found. Here’s an example of popping an element with only the required […]

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Advanced, Classification, NLP, Project, R, Social Media, Technique, Text, Unstructured Data, Unsupervised Leave a comment

Customer Sentiments Analysis of Pepsi and Coca-Cola using Twitter Data in R

This article was published as a part of the Data Science Blogathon. Introduction Coca-Cola and PepsiCo are well-established names in the soft drink industry with both in the fortune 500. The companies that own a wide spectrum of product lines in a highly competitive market have a fierce rivalry with each other and constantly competing for market share in almost all subsequent product verticals. We will analyze the sentiment of customers of these two companies with the help of 5000 […]

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Machine Learning

How to Use Optimization Algorithms to Manually Fit Regression Models

Regression models are fit on training data using linear regression and local search optimization algorithms. Models like linear regression and logistic regression are trained by least squares optimization, and this is the most efficient approach to finding coefficients that minimize error for these models. Nevertheless, it is possible to use alternate optimization algorithms to fit a regression model to a training dataset. This can be a useful exercise to learn more about how regression functions and the central nature of […]

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Machine Learning

How to Develop a Neural Net for Predicting Disturbances in the Ionosphere

It can be challenging to develop a neural network predictive model for a new dataset. One approach is to first inspect the dataset and develop ideas for what models might work, then explore the learning dynamics of simple models on the dataset, then finally develop and tune a model for the dataset with a robust test harness. This process can be used to develop effective neural network models for classification and regression predictive modeling problems. In this tutorial, you will […]

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NLP, single bridge language

Issue #117 – Subword Segmentation and a Single Bridge Language Affect Zero-Shot Neural Machine Translation

11 Feb21 Issue #117 – Subword Segmentation and a Single Bridge Language Affect Zero-Shot Neural Machine Translation Author: Dr. Jingyi Han, Machine Translation Scientist @ Iconic Introduction Nowadays, zero-shot machine translation is receiving more and more attention due to the expensive cost of building new engines for different language directions. The underlying principle of this strategy is to build a single model that can learn to translate between different language pairs without involving direct training for such combinations. Following the […]

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NLP

Hugging Face – Issue 7 – Feb 9th 2021

News New Year, New Website! Our vision for the future of machine learning is one step closer to reality thanks to the 1,000+ researchers & open-source contributors, thousands of companies & the fantastic Hugging Face team! Last month, we announced the launch of the latest version of huggingface.co and we couldn’t be more proud. 🔥 Play live with >10 billion parameters models for tasks including translation, NER, zero-shot classification, and

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