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The Augmented Scientist Part 1: Practical Application Machine Learning in Classification of SEM Images
Our goal here is to see if we can build a classifier that can identify patterns in Scanning Electron Microscope (SEM) images, and compare the performance of our classifier to the current state-of-the-art.
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Hands on Hyperparameter Tuning with Keras Tuner
Or how hyperparameter tuning with Keras Tuner can boost your object classification network's accuracy by 10%.
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Introducing fastpages: An easy to use blogging platform with extra features for Jupyter Notebooks
This article introduces the easy to use blogging platform fastpages. fastpages relies on Github pages for hosting, and Github Actions to automate the creation of your blog, and contains extra features for Jupyter Notebooks.
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Image Recognition and Object Detection in Retail
“According to Gartner, by 2020, 85% of customer interactions in the retail industry will be managed by AI.”
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How Kubeflow Can Add AI to Your Kubernetes Deployments
As Kubernetes is capable of working with other solutions, it is possible to integrate it with a collection of tools that can almost fully automate your development pipeline. Some of those third-party tools even allow you to integrate AI into Kubernetes. One such tool you can integrate with Kubernetes is Kubeflow. Read more about it here.
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The Forgotten Algorithm
This article explores Monte Carlo Simulation with Streamlit.
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Using the Fitbit Web API with Python
Fitbit provides a Web API for accessing data from Fitbit activity trackers. Check out this updated tutorial to accessing this Fitbit data using the API with Python.
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Using AI to Identify Wildlife in Camera Trap Images from the Serengeti
With recent developments in machine learning and computer vision, we acquired the tools to provide the biodiversity community with an ability to tap the potential of the knowledge generated automatically with systems triggered by a combination of heat and motion.
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Introduction to Geographical Time Series Prediction with Crime Data in R, SQL, and Tableau
When reviewing geographical data, it can be difficult to prepare the data for an analysis. This article helps by covering importing data into a SQL Server database; cleansing and grouping data into a map grid; adding time data points to the set of grid data and filling in the gaps where no crimes occurred; importing the data into R; running XGBoost model to determine where crimes will occur on a specific day
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Practical Hyperparameter Optimization
An introduction on how to fine-tune Machine and Deep Learning models using techniques such as: Random Search, Automated Hyperparameter Tuning and Artificial Neural Networks Tuning.
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