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Automatic Content Tagging using NLP and Machine Learning
In this article, we will explore how content tagging can be automated with the help of NLP. I will also go into the details of what resources you will need to implement such a system and what approach is more favorable for your case. A few years back, I have developed an automated tagging system…
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Fraud detection using Machine learning
Fraud Detection as classification problem To illustrate how fraud detection problem can be solved using Machine learning I will use data available on kaggle : https://www.kaggle.com/mlg-ulb/creditcardfraudThe purpose of this article is to discuss the biggest challenges in predicting fraudulent data and how to overcome those. In Machine Learning, problems like fraud detection are typically framed…
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Your Machine Learning project needs good Data. How to solve the problem of lack of data?
Machine learning applications are reliant on, and sensitive to, the data they train on. These most excellent practices will help you ensure that training data is of high quality. To be efficient, machine learning (ML) need a significant amount of data. We can anticipate a child to comprehend what a feline is and identify other…
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Guided analytics are the future of Data Science and AI
Nowadays, people are used to and take it for granted, the added value in their life, from using Siri, or Google’s Assistant or Alexa for all sorts of things: answering odd trivia concerns, inspecting the weather condition, purchasing groceries, getting driving instructions, turning on the lights, and even inspiring a dance celebration in the cooking…
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Important things to consider before building your machine learning and AI project
Current State of the market In order to go in-depth on what exactly data science and machine learning (ML) tools or platforms are, why companies small and large are moving toward them, and why they matter in the Enterprise AI journey, it’s essential to take a step back and understand where we are in the…
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Making Machine Learning more efficient with the cloud
In the essence, machine learning is a productivity tool for data scientists. As the heart of systems that can learn from data, machine learning permits data scientists to train design on an example data set and then utilize algorithms that immediately generalize and find out both from that example and from new data feeds. With…
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Machine Learning in the cloud
As artificial intelligence (ML) and also artificial intelligence come to be extra prevalent, data logistics will be vital to your success.While building Machine Learning projects, most of the effort required for success in artificial intelligence is not the algorithm, design, structure, or the learning itself. It’s the data logistics. Perhaps less amazing than these other…
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How to boost your Machine learning model accuracy
There are multiple ways to boost your predictive model accuracy. Most of these steps are really easy to implement, but yet for many reasons data scientist fail to do proper data preparation and model tuning. in the end, they end up with average or below average machine learning models. Having domain knowledge will give you…
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Personalization – How much do you understand your customer?
Every day we are trying to better understand our customers. Directly or indirectly. Consciously or unconsciously. All marketing activities that are organized for us, all the offers that we receive on our emails, apps, banner ads, billboards on the bus stations, hidden messages in the last movie you watched or message to buy pairing product.…
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What kind of hacking skills does a data scientist require and how to get them?
I have been asked really often what should I know to become a Data Scientist? I have written before but I’ll try to put again some more info to help the people who really want to go that path. Free Tools can help a lot for start! There are many tools that can help you…
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Data Science Tips 