Descriere YEO:
Pe YEO găsești Cracking the Data Science Interview: de la Independently Published, în categoria Foreign Books.
Indiferent de nevoile tale, Cracking the Data Science Interview: 101+ Data Science Questions & Solutions, Paperback/Maverick Lin din categoria Foreign Books îți poate aduce un echilibru perfect între calitate și preț, cu avantaje practice și moderne.
Preț: 49.71 Lei
Caracteristicile produsului Cracking the Data Science Interview:
- Brand: Independently Published
- Categoria: Foreign Books
- Magazin: elefant.ro
- Ultima actualizare: 05-12-2024 01:40:20
Comandă Cracking the Data Science Interview: Online, Simplu și Rapid
Prin intermediul platformei YEO, poți comanda Cracking the Data Science Interview: de la elefant.ro rapid și în siguranță. Bucură-te de o experiență de cumpărături online optimizată și descoperă cele mai bune oferte actualizate constant.
Descriere magazin:
Cracking the
Data Science Interview is the first book that attempts to capture the essence of data science in a concise, compact, and clean manner. In a
Cracking the Coding
Interview style,
Cracking the
Data Science Interview first introduces the relevant concepts, then presents a series of interview questions to help you solidify your understanding and prepare you for your next interview. Topics include: - Necessary Prerequisites (statistics, probability, linear algebra, and computer science) - 18 Big Ideas in
Data Science (such as Occam\'s Razor, Overfitting, Bias/Variance Tradeoff, Cloud Computing, and Curse of Dimensionality) - Data Wrangling (exploratory data analysis, feature engineering, data cleaning and visualization) - Machine Learning Models (such as k -NN, random forests, boosting, neural networks, k -means clustering, PCA, and more) - Reinforcement Learning (Q-Learning and Deep Q-Learning) - Non-Machine Learning Tools (graph theory, ARIMA, linear programming) - Case Studies (a look at what data science means at companies like Amazon and Uber)
Maverick holds a bachelor\'s degree from the College of Engineering at Cornell University in operations research and information engineering (ORIE) and a minor in computer science. He is the author of the popular Data Science Cheatsheet and Data Engineering Cheatsheet on GCP and has previous experience in data science consulting for a Fortune 500 company focusing on fraud analytics.