9798257059346 - foundations of machine learning: a practitioner's journey — from mathematical foundations to classical algorithms: 1 di dharmalingam, mr krishna (6 risultati)
Lingua: Inglese
Editore: Independently published, 2026
- Brossura
Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 38,94
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Independently published, 2026
- Brossura
Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 33,66
EUR 6,85 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Independently Published Apr 2026, 2026
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 50,00
EUR 64,44 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. Neuware - The first volume of A Practitioner's Journey. Eighteen chapters take you from linear algebra and probability through every classical machine-learning algorithm worth knowing - regression, trees, ensembles, SVMs, KNN, time series, and recommendation systems - with the math, the intuition, a…nd runnable code, all in one place.
Lingua: Inglese
Editore: Independently published, 2026
- Brossura
- Print on Demand
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 33,59
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Independently Published, 2026
- Brossura
- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 37,71
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. The first volume of A Practitioner's Journey. Eighteen chapters take you from linear algebra and probability through every classical machine-learning algorithm worth knowing - regression, trees, ensembles, SVMs, KNN, time series, and recommendation systems - with the math, the intuition, an…d runnable code, all in one place.This is the curriculum a working ML practitioner actually needs. Most "intro to ML" books pick a side: pure math with no code, or library-call tutorials that fall apart the moment you try to apply them. Foundations of Machine Learning refuses both. Every chapter is built around a working scenario. Every code example runs. Every concept comes with both the math and the intuition.You will learn to: Reason about linear algebra, calculus, probability, and optimization the way ML uses themDerive and implement classical algorithms from first principles, not as library callsChoose the right algorithm for the right problem and explain whyEvaluate models honestly, avoid overfitting, and know when "good enough" is good enoughApply the CRISP-DM framework to a real end-to-end case studyCompanion volumes: Book 2 Machine Learning in Production covers deep learning, computer vision, and the production engineering stack. Book 3 Artificial Intelligence in Production covers LLMs, RAG, agents, and modern AI infrastructure. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Independently Published, 2026
- Brossura
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 37,84
EUR 43,17 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. The first volume of A Practitioner's Journey. Eighteen chapters take you from linear algebra and probability through every classical machine-learning algorithm worth knowing - regression, trees, ensembles, SVMs, KNN, time series, and recommendation systems - with the math, the intuition, an…d runnable code, all in one place.This is the curriculum a working ML practitioner actually needs. Most "intro to ML" books pick a side: pure math with no code, or library-call tutorials that fall apart the moment you try to apply them. Foundations of Machine Learning refuses both. Every chapter is built around a working scenario. Every code example runs. Every concept comes with both the math and the intuition.You will learn to: Reason about linear algebra, calculus, probability, and optimization the way ML uses themDerive and implement classical algorithms from first principles, not as library callsChoose the right algorithm for the right problem and explain whyEvaluate models honestly, avoid overfitting, and know when "good enough" is good enoughApply the CRISP-DM framework to a real end-to-end case studyCompanion volumes: Book 2 Machine Learning in Production covers deep learning, computer vision, and the production engineering stack. Book 3 Artificial Intelligence in Production covers LLMs, RAG, agents, and modern AI infrastructure. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
