In today’s episode, Gregory Glatzer explained his machine learning project that involved the prediction of elephant movement and settlement, in a bid to limit the activities of poachers. He used two machine learning algorithms, DBSCAN and K-Means clustering at different stages of the project. Listen to learn about why these two techniques were useful and what conclusions could be drawn.
Neural Architecture Search for CTR Prediction
Algorithmic PPC Management
Data Skeptic: Ad Tech
The Reliability of Mobile Phone Data
Haywire Algorithms
School Reopening Analysis
Modern Data Stacks
Emoji as a Predictor
Polarizing Trends in the Gig Economy
Remote Learning in Applied Engineering
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Learning Digital Fabrication Remotely
Remote Software Development
Quantum K-Means
K-Means in Practice
Fair Hierarchical Clustering
Matrix Factorization For k-Means
Breathing K-Means
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