qualitative data analysis

Vector Databases - by Nitin Borwankar (Paperback)

Machine Learning Design Patterns - by Valliappa Lakshmanan & Sara Robinson & Michael Munn (Paperback)

Analytical Skills for AI and Data Science - by Daniel Vaughan (Paperback)

Practical Linear Algebra for Data Science - by Mike X Cohen (Paperback)

Unifying Business, Data, and Code - by Ron Itelman & Juan Cruz Viotti (Paperback)

Practical Time Series Analysis - by Aileen Nielsen (Paperback)

Data Mesh - by Zhamak Dehghani (Paperback)

Automating Data Quality Monitoring - by Jeremy Stanley & Paige Schwartz (Paperback)

Programming Pytorch for Deep Learning - by Ian Pointer (Paperback)

Building Green Software - by Anne Currie & Sarah Hsu & Sara Bergman (Paperback)

Data Engineering for Multimodal AI - by Vasundra Srinivasan (Paperback)

Head First Algorithms and Data Structures - by Eric Freeman & Elisabeth Robson (Paperback)

Learning MySQL - 2nd Edition by Vinicius M Grippa & Sergey Kuzmichev (Paperback)

Developing Apps with GPT-4 and ChatGPT - 2nd Edition by Olivier Caelen & Marie-Alice Blete (Paperback)

Kubernetes: Up and Running - 3rd Edition by Brendan Burns & Joe Beda & Kelsey Hightower & Lachlan Evenson (Paperback)

Essential Math for AI - by Hala Nelson (Paperback)

Evals for AI Engineers - by Shreya Shankar & Hamel Husain (Paperback)

Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow - 3rd Edition by Aurélien Géron (Paperback)

Deciphering Data Architectures - by James Serra (Paperback)

Applied Machine Learning and AI for Engineers - by Jeff Prosise (Paperback)

Deep Learning for Coders with Fastai and Pytorch - by Jeremy Howard & Sylvain Gugger (Paperback)

Machine Learning Interviews - by Susan Shu Chang (Paperback)

Generative AI on AWS - by Chris Fregly & Antje Barth & Shelbee Eigenbrode (Paperback)

Hands-On Generative AI with Transformers and Diffusion Models - by Omar Sanseviero & Pedro Cuenca & Apolinário Passos & Jonathan Whitaker