Machine Learning: Dimensionality Reduction via Linear Discriminant Analysis
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. A machine learning algorithm (such as classification, clustering or regression) uses a training dataset to determine weight factors that can be applied to unseen data for predictive purposes. Before implementing a machine …
Where the randomness comes
Author(s): Jun Wang Originally published on Towards AI. Word Embedding and Language Modeling U+007C Towards AI How to Get Deterministic word2vec/doc2vec/paragraph Vectors OK, welcome to our Word Embedding Series. This post is the first story of the series. You may find this …
Developing ‘mini-brains’ With the Help of Machine Learning
Producing novel treatments for psychological disorders with the help of machine learning Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Machine Learning: Dimensionality Reduction via Principal Component Analysis
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. How does PCA work? In machine learning, a dataset containing features (predictors) and discrete class labels (for a classification problem such as logistic regression); or features and continuous outcomes (for a linear …
Machine Learning (ML) vs. Artificial Intelligence (AI)—Crucial Differences
Machine Learning Open License — Image Credits: IoT World Today Unfortunately, some tech organizations are deceiving customers by proclaiming to use machine learning (ML) and artificial intelligence (AI) on their technologies while not being clear about their products’ limits. Helping Scale AI & Technology Startups …
Amazon Scraps Secret AI Recruiting Engine that Showed Biases Against Women
Credit: The Verge | “It is the mission of our generation to build fair AI.” ~ Omar U. Florez Distinguished Professor Stuart Evans mentioned during a lecture at Carnegie Mellon University how biases in machine learning algorithms can negatively affect our society, whether …
The Best Public Datasets for Machine Learning and Data Science
Author(s): Stacy Stanford, Roberto Iriondo, Pratik Shukla Best Public Datasets for Machine Learning and Data Science Best open-access datasets for machine learning, data science, sentiment analysis, computer vision, natural language processing (NLP), clinical data, and others. This resource is continuously updated. If you …
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