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    Techniques for Collecting, Prepping, and Plotting Data: Predicting Social Media-Influence in the NBA

    This article provides insight on the mindset, approach, and tools to consider when solving a real-world ML problem. It covers questions to consider as well as collecting,...

    Clustering in R

    This article covers clustering including K-means and hierarchical clustering. A complementary Domino project is available. Introduction Clustering is...
    Addison-Wesley Professional Code Data Science Featured Machine Learning Hierarchical Clustering Clustering Practical Techniques R Partitioning Around Medoids data PAM K-medoids K-means clustering

    Understanding Causal Inference

    This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data...
    Addison-Wesley Professional Data Science Causal Inference Model Management Machine Learning Practical Techniques Python Model Context Model Development

    Time Series with R

    This article delves into methods for analyzing multivariate and univariate time series data. A complementary Domino project is available. Introduction
    Addison-Wesley Professional Data Science Code Autocorrelation ARMA Practical Techniques R GARCH Time Series Practical Techniques Featured data model

    Exploring US Real Estate Values with Python

    This post covers data exploration using machine learning and interactive plotting. If interested in running the examples, there is a complementary...
    Addison-Wesley Professional Data Science Code Machine Learning Practical Techniques Plotly Dash Python Data Visualization Pandas Cufflinks data

    Deep Reinforcement Learning

    This article provides an excerpt "Deep Reinforcement Learning" from the book, Deep Learning Illustrated by Krohn, Beyleveld, and Bassens. The article...
    Addison-Wesley Professional Data Science Code Machine Learning Keras Models Featured Deep Q-Learning Practical Techniques DQN Reinforcement Learning Deep Learning

    Towards Predictive Accuracy: Tuning Hyperparameters and Pipelines

    This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E....
    Addison-Wesley Professional Data Science Code Model Management Machine Learning sklearn Models Featured Practical Techniques Model Evaluation Python KNeighborsClassifier Hyperparameters Model Context RandomizedSearch Tuning Hyperparameters Model Development K-NN GridSearch model

    Deep Learning Illustrated: Building Natural Language Processing Models

    Many thanks to Addison-Wesley Professional for providing the permissions to excerpt "Natural Language Processing" from the book, Deep Learning...
    Addison-Wesley Professional Data Science Code Machine Learning Machine Learning Featured Word2vec word embeddings Practical Techniques Recurrent Neural Networks RNN NLP Deep Learning ROC AUC Metric Convolutional Networks Dense Network

    Manual Feature Engineering

    Many thanks to AWP Pearson for the permission to excerpt "Manual Feature Engineering: Manipulating Data for Fun and Profit" from the book, Machine...
    Addison-Wesley Professional Data Science Code Engineering Model Management Machine Learning Practical Techniques Feature Engineering data model

    Machine Learning in Production: Software Architecture

    Special thanks to Addison-Wesley Professional for permission to excerpt the following "Software Architecture" chapter from the book, Machine Learning...
    Addison-Wesley Professional Engineering Model Management Machine Learning Software Architecture Data Science and Data Engineering Alignment Practical Techniques Model Production Data Engineering Data Infrastructure Data Scientists

    Manipulating Data with dplyr

    Special thanks to Addison-Wesley Professional for permission to excerpt the following "Manipulating data with dplyr" chapter from the book, ...
    Addison-Wesley Professional Data Science Code Practical Techniques R dplyr Model Development
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