Alongside the rise of the internet came the growth of self-learning. Self-learning has never been easier than in the 21st Century as a result of Massive Open Online Courses (MOOCs) that are distributed globally via the internet. These courses have grown in popularity to the point where some are even questioning the credibility of the academic system that has influenced many businesses hiring strategies in the corporate world.
I’ve personally taken my fair share of MOOCs — I still do now. Undoubtedly, I would concur that these courses are priceless, well at least some of them. No pun intended.
Whenever we build Machine Learning models, we need some form of metric to measure the goodness of the model. Bear in mind that the “goodness” of the model could have multiple interpretations, but generally when we speak of it in a Machine Learning context we are talking of the measure of a model's performance on new instances that weren’t a part of the training data.
Determining whether the model being used for a specific task is successful depends on 2 key factors:
It’s highly unlikely that business owners are going to read this and begin to change their perspectives on how we define Data Science. Not because I doubt my influence or anything, but since I’m aware that the majority of my readers are at the beginning of their Data Science journey — I really dislike the term “aspiring” — but here is what I wish to tell you all…
Stop trying to be good at everything in Data Science, and pick 1 (max 2) area’s you want to specialize in and get really good at it!
Let’s face it... Breaking into…
Deep Learning; The solution to the problems of mankind. Over the past few years, Deep Learning has advanced humanity in novel ways. One of these beneficiaries is the entire field of Natural Language Processing (NLP). But before we get into how, let’s explore the field of Deep Learning.
I’m pretty sure we’ve all seen the Venn diagram that illustrates the relationship of Artificial Intelligence (AI) to Machine Learning (ML) to deep learning. If not, it simply demonstrates that Deep Learning is a subfield of Machine Learning which is a subfield of Artificial Intelligence.
How Deep Learning differs from Machine Learning…
Books are truly my lifeblood; I’d consider myself an avid book worm, but I must retract that statement whenever it comes to technical books. For some strange reason, technical books always make me feel more sleepy rather than interested.
However, in the past, I’ve managed to conjure up the strength to keep my eyelids open and get through these books. Something I’ve realized is that whenever I have done that, I’ve made massive progress in the subject or area I’m studying, hence this month I’ll be doing it again.
Artificial Intelligence is rapidly creeping into the workflow of many businesses across various industries and functions. Due to advancements in Natural Language Processing (NLP), Natural Language Understanding (NLU), and Machine Learning (ML), humans are now able to develop technologies that are capable of imitating human-like interactions which include recognizing speech, as well as text.
In this article, we are going to build a Chatbot using NLP and Neural Networks in Python.
Before we can begin to think of any coding, we need to set up an intents JSON file that defines certain intentions that could occur during the interactions with…
I’m sure we’ve all been in a position where we’ve tried to contact our bank, but before we can speak to an assistant, we have to go through some sort of automated system. How annoying is it when these systems simply can’t understand us? After minutes of back and forths and struggling to understand the system refers us to a real person to handle our query and take us through the exact same process.
If we are going to be having conversations with a computer, we’d at least want for it to replicate a human interaction as much…
I don’t know where I’d be right now if it wasn’t for Youtube tutorials — I literally use them for everything, i.e. Improving communication skills, learning how to do new calisthenics tricks, how to get more matches on Tinder, and many other things.
There are some special channels that have helped me immensely in my Data Science development and I believe it’s important I share them with you. Brace Yourself.
Data Science dream job is all about getting hired. This channel will teach you all the necessary things you need to do to get hired and to progress…
Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data [Source: Wikipedia].
If you’ve decided that NLP is the subfield of Data Science you wish to specialize your skills in, the next step is identifying the key areas you need to understand to progress your career. …
Consider the following 2 sentences:
A human could easily determine that these 2 sentences convey a very similar meaning despite being written in 2 completely different formats; The intersection of the 2 sentences only has one word in common, “is”, and it doesn’t provide any insight into how similar the sentences. Nonetheless, we’d still expect a similarity algorithm to return a score that informs us that the sentences are very similar.
This phenomenon describes what we’d refer to as semantic text similarity, where we aim to identify how similar documents are…
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