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Weekly Selection – Oct 26, 2018

The 5 Basic Statistics Concepts Data Scientists Need to Know

By George Seif – 9 min read

Statistics can be a powerful tool when performing the art of Data Science (DS). From a high-level view, statistics is the use of mathematics to perform technical analysis of data.


AI Insights for Human Intelligence

By Mehmet Alican Noyan – 8 min read

Comparison between artificial intelligence (AI) and human intelligence has been a heated debate ever since Turing envisioned thinking machines


Transfer learning from pre-trained models

By Pedro Marcelino – 14 min read

Deep learning is fast becoming a key instrument in artificial intelligence applications (LeCun et al. 2015). For example, in areas such as computer vision, natural language processing, and speech recognition, deep learning has been producing remarkable results.


Lessons Learned from Applying Deep Learning for NLP Without Big Data

By yonatan hadar – 10 min read

As a data scientist, one of your most important skills should be choosing the right modeling techniques and algorithms for your problems. A few months ago I was trying to solve a text classification problem of classifying which news articles will be relevant for my customers.


Building an ETL Pipeline in Python

By Daniel Foley – 8 min read

In my last post, I discussed how we could set up a script to connect to the Twitter API and stream data directly into a database. Today, I am going to show you how we can access this data and do some analysis with it, in effect creating a complete data pipeline from start to finish.


Text Predictor – Generating Rap Lyrics with Recurrent Neural Networks (LSTMs)

By Greg Surma – 12 min read

In today’s article, I am going to introduce you to the topic of Recurrent Neural Networks (RNNs), which will allow us to train agents that learn on sequential data like text, audio, video, etc.


NeuralFunk – Combining Deep Learning with Sound Design

By Max Frenzel – 21 min read

For a long time now I have wanted to combine my passion for music with my work in artificial intelligence. But I kept putting it off. I felt that I needed to improve my music production skills first before trying to get deep learning involved in the process.


SQL at Scale with Apache Spark SQL and DataFrames – Concepts, Architecture and Examples

By Dipanjan (DJ) Sarkar – 21 min read

Relational Databases are here to stay, regardless of the hype as well as the advent of newer databases often popularly termed as ‘NoSQL’ databases. The simple reason is that these databases enforce essential structure, constraints and provide a nice declarative language to query data which we love – SQL!


How I Exploited My Own Social Media Data

By Jessie Smith – 5 min read

About two years ago I took my first introductory data science course. Throughout the duration of the ten weeks that I was enrolled, I learned how to scrape data, modify it, analyze it, visualize it, and stick it into machine learning algorithms.


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