Liz Waldner's bold new collection takes its title and its inspiration from Definition 1 of Euclid's Elements of Geometry. Its six sections—point, line, circle, square, triangle, and point again—are explorations of various kinds of longing and loss—sex, death, exile, story, love, and time. Drawing from culture high and low—Eno and Aquinas, Lassie and Donne, Silicon Valley and Walden Pond—these poems offer proof of and proof against the “mortal right-lined circle” of memory and identity. The innocence and Keatsian beauty of Euclid's geometry become poignant from a perspective that encompasses all that is non-Euclidean as well as space, time, and the theory of matter. With rare wit and linguistic daring, Waldner opens resonant channels of communication that show there is indeed more than meets the eye—or the mind—in her poems. Hand to Mouth (Twist and Shout) Cold comes slow up out of the darkness among the leaves that smell so good when bruised Do you, too, recognize me god so soon? Her First Reckoning Pour wine into vessels the violet of woods, wine of the reddening stars. You are god, you can do it. Your lover calls you St. John the Conqueror. I have heard her. This is the name of a root. Asperge the thousands and thousands of rooms in which photosynthesis promises sun to the acolyte cells. Rain yourself on a leaf. Birch. The bark is malleable as mushroom flesh. Show that you know me. Scratch out my name with this tree. My name of trees. On the day I arrive at the door of my death, myself now hard to tell from the trees that had hid it from me, I will demand that you love me. You made me like this. Why did you make me like this? Transitive, Intransitive: Extemporary Measures Two crows above the marsh: sew. Stitch the seventeen sleek shades of blue to the shadow-patterned greens below. See fit to make me a suitable view who having nowhere to else to go might as well wear this world well. Llama necks periscope the view: yonder, across the water, you testing the air now a crow chases a redwing blackbird through. What can I show you who sees I don't believe? For now, what the eye of the needle sees: through through through: clouds, birds, me, trees; soon: in, out, with, to; something moving, something moved: a stitch in time's an avenue, future's sutures' revenue— “the shining hour” improved.

"The book includes introductions, terminology and biographical notes, bibliography, and an index and glossary" --from book jacket.

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.