Friday, May 1Digital Marketing Journals

data-science

Is Natural Language Processing a good career? | by Bdour Zeer
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Is Natural Language Processing a good career? | by Bdour Zeer

Photo by Christopher Gower on UnsplashIn recent years and in 2022, many new roles and job descriptions emerged in the tech world, one of them is NLP Researcher, NLP Engineer or NLP Analysts. So you might ask yourself whether this new role is a good career option for you and if you should major in it. In this article I will break down with you:What does NLP mean ?What does an NLP engineer do?How much money does an NLP engineer make in 2022?What degrees do you need & the skills you must have?What are the open free resources for you to self study and learn more about natural language processing?Is it worth investing in NLP as a career and major?First of all let us properly introduce natural language processing and what do we mean by it:NLP is how computers deal with mainly textual data (h...
Good Risk vs Bad Risk: Deconstructing the Features of 1000 German Loans | by Paul Suddon
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Good Risk vs Bad Risk: Deconstructing the Features of 1000 German Loans | by Paul Suddon

In every business, it is important to understand your customers but no more so than in the world of finance — where the stakes are comparatively much higher. For a bank, each customer presents a risk, especially when it comes to loaning money. Bad loans are full of risk, good loans are not. Ultimately, deciding whether that risk is worth taking is a decision of paramount importance and can affect the bank balances of people the world over.Investment in risky loans is more likely to end up with customers defaulting on their payments — the consequences of this have been made painfully clear in recent history.With this kind of responsibility at stake, banks tend to analyse their customer’s finances with the utmost scrutiny. Loans are granted — only — when an applicant meets certain criteria. ...
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Build a Chatbot about your favorite series in 30 minutes

Expand your NLP portfolio using BERT and Haystack to answer all your questions!If you’re trying to learn Natural Language Processing (NLP), make a Discord Bot, or are just interested to play around with Transformers for a bit, this is the project for you!In this example, we will create a Chatbot that knows everything about Dragon Ball, but you can do about anything you want! It can be a chatbot that answers questions about another series, a university course, the laws of a country, etc. Firstly, let’s see how that is possible with BERT.How a BERT works as a ChatbotBERT is a Machine Learning technique for NLP created and published by Google in 2018. In the first phase, the model is pre-trained on a large language dataset in a semi-supervised way.In this phase, the model cannot answer questi...
Let Them Eat CakeChat. CakeChat, released by the Replika team… | by Evan SooHoo | Jan, 2022
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Let Them Eat CakeChat. CakeChat, released by the Replika team… | by Evan SooHoo | Jan, 2022

Photo by Markus Winkler on UnsplashThere are two ways to approach software development: Top-down, and bottom-up. This is mostly me taking poetic license over academic terms that mean something else, but coding interviews today have a very “bottom-up” approach to assessing software competence. They assign coding tests, likely piggy-backing off of containerization technology like Docker, and they ask interviewees to build their own self-contained programs that run only on the code they can whip up in a few minutes. They do not have to spend time setting up their environments. They do not have to customize their configuration files, or download dependencies that are necessary for other dependencies. They just code, and tests are run automatically. In some cases candidates only get a plain tex...
QnA Chatbot using sentence simi. Introduction | by AI Brewery
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QnA Chatbot using sentence simi. Introduction | by AI Brewery

When the user enters the query:1. Calculate the sentence vector of the query2. Identify the most matching sentence from the knowledge base using cosine similaritydef calculate_similarity(query):mean_pooled = get_embedding([query]) question = []similarity = []intent = [] for rec in collection.find():question.append(rec[‘Text’])intent.append(rec[‘Intent’])cos_sim = cosine_similarity([mean_pooled[0]],[np.fromiter(rec[‘Embedding’], dtype=np.float32)]) similarity.append(cos_sim) index = np.argmax(similarity)recognized_intent = intent[index]return recognized_intentIntents JSON fileHere we set up an intents JSON file that defines the intentions of the chatbot user.For example:A user may wish to know the name of our chatbot; therefore, we have created an intent called name.A user may wish to kn...
5 Reasons not to use Data (and why Most are BS) | by Amit Bhardwaj | Nov, 2021
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5 Reasons not to use Data (and why Most are BS) | by Amit Bhardwaj | Nov, 2021

If you are a data person by which I mean you use data or facilitate data to others for their use so that others can make “data-informed” decisions on an almost daily basis then you might have come across many scenarios where data is just overhead and sometimes using data even might be an overkill.So imagine a situation where a person who is not aware of many aspects of data and how it can be utilised how much overwhelming it can be for them, right?Business, product and engineering all, need to come together to get the right information from data, which means essentially tons of meetings, documentation and finally, the intuition-based decision is taken, which means why to use data in the first place.Here are the top 6 excuses I have seen why not to use data — and simple solutions to get mov...
Evaluating classification models. Accuracy, Precision and Recall. | by Manuel Gil | Jul, 2021
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Evaluating classification models. Accuracy, Precision and Recall. | by Manuel Gil | Jul, 2021

In this article, I am going to delve into some metrics used to measure how well classifiers do their job. So after reading this article you will know how to evaluate classification models and know the difference between the different metrics that we can encounter evaluating classifier models.In the image shown above, we can see a classification problem. How can we know if this model is good or bad? Let’s delve into this in the following paragraphs.The goal of each classifier is to assign one label to one input according to their characteristics, in other words, classifiers can distinguish the instances belonging to different categories. But how can we measure how well a classifier performs this task?The first idea that comes to our minds is probably to calculate the ratio between the corre...
Voice Personalization. For a given text in any language or… | by Sangramsing Kayte | Jul, 2021
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Voice Personalization. For a given text in any language or… | by Sangramsing Kayte | Jul, 2021

The language characteristics derived from a certain text are mapped on acoustic features via a GANs-based TTS system.The features of the linguistic input include binary answers to linguistic context questions and numerical values, such as the number of words in the current sentence, the position of the current syllable in the word, and the length of the current phoneme.The acoustic features consist of melted cepstral coefficients and exciting parameters and of the basic frequency. The neural network parameters can be trained by using the input and output pairs derived from a training data set. Finally, a WORLD vocoder is used to synthesize speech from the acousticfeatures. The proposed model consists of two components as follow:Emotional Analysis Module:-The goal of this module is the diff...
Build an Application Digital History using Natural Language Processing | by Sangramsing Kayte | Jun, 2021
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Build an Application Digital History using Natural Language Processing | by Sangramsing Kayte | Jun, 2021

With the historical text data, images data or speech data, we can build an application that will help to understand the historical terms more effectively and will also broad line the visuals if needed. Using Natural Language Processing techniques like named entity recognition, part-of-speech tagging we can aim for text summarization with the clear perspective of explaining the historical terms. The report can be generated which could be further utilized for analysis for specific incident or event. During learning history, I felt hard to pronounce the names of kingdom and rulers. Thus, we can apply, listen and speak button for difficult words in the document. This will help the user to understand the terms easily. We can also provide visuals for a specific event or specific dates. There are...
Knowledge bots. Earlier this year, I had a task to… | by Abhinav Ajmera | Apr, 2021
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Knowledge bots. Earlier this year, I had a task to… | by Abhinav Ajmera | Apr, 2021

Earlier this year, I had a task to create a knowledge bot for an enterprise level platform. The users were primarily the employees of the organization and intention was to use the knowledge bot to share the offering and usage of platform.There are quite a lot of frameworks in the market (each with its own pros and cons) hence it is very important that one selects the right framework depending upon the kind of bot that you are targeting to create. In case of creating the knowledge bots the typical requirements are –1. The main purpose of the knowledge bot is to provide the information about the offering via a guided chat. If the user wishes, he should be able to come out of the guided chat and ask adhoc questions about the offering and go back to the guided chat.2. The knowledge bot should ...