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Creating a Simple Z-test Calculator using Streamlit

Analytics Vidhya

Statistics plays an important role in the domain of Data Science. It is a significant step in the process of decision making, powered by Machine Learning or Deep Learning algorithms. One of the popular statistical processes is Hypothesis Testing having vast usability, not […].

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A Practitioner’s Guide to Deep Learning with Ludwig

Domino Data Lab

New tools are constantly being added to the deep learning ecosystem. For example, there have been multiple promising tools created recently that have Python APIs, are built on top of TensorFlow or PyTorch , and encapsulate deep learning best practices to allow data scientists to speed up research. Introduction.

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A Deep Dive into LSTM Neural Network-based House Rent Prediction

Analytics Vidhya

Introduction Long Short Term Memory (LSTM) is a type of deep learning system that anticipates property leases. Rental markets are influenced by diverse factors, and LSTM’s ability to capture and remember […] The post A Deep Dive into LSTM Neural Network-based House Rent Prediction appeared first on Analytics Vidhya.

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SiftSeq: Classifying short DNA sequences with deep learning

Insight

In this post, I demonstrate how deep learning can be used to significantly improve upon earlier methods, with an emphasis on classifying short sequences as being human, viral, or bacterial. As I discovered, deep learning is a powerful tool for short sequence classification and is likely to be useful in many other applications as well.

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AI adoption in the enterprise 2020

O'Reilly on Data

Supervised learning is the most popular ML technique among mature AI adopters, while deep learning is the most popular technique among organizations that are still evaluating AI. Key survey results: The majority (85%) of respondent organizations are evaluating AI or using it in production [1]. But what kind? It ranks high (No.

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The unreasonable importance of data preparation

O'Reilly on Data

If a self-driving car’s decision-making algorithm is trained on data of traffic collected during the day, you wouldn’t put it on the roads at night. To take it a step further, if such an algorithm is trained in an environment with cars driven by humans, how can you expect it to perform well on roads with other self-driving cars?

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Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production. Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision.