AI & Art
@Machine_learn
some artist use the large collections of #data & #ML #algorithms to create mesmerizing & dynamic #installations
watch the video —> https://youtu.be/I-EIVlHvHRM
@Machine_learn
some artist use the large collections of #data & #ML #algorithms to create mesmerizing & dynamic #installations
watch the video —> https://youtu.be/I-EIVlHvHRM
YouTube
How This Guy Uses A.I. to Create Art | Obsessed | WIRED
Artist Refik Anadol doesn't work with paintbrushes or clay. Instead, he uses large collections of data and machine learning algorithms to create mesmerizing and dynamic installations.
Machine Hallucination at Artechouse NYC: https://www.artechouse.com/nyc…
Machine Hallucination at Artechouse NYC: https://www.artechouse.com/nyc…
Build_a_Career_in_Data_Science_by_Emily_Robinson,_Jacqueline_Nolis.pdf
12.3 MB
Build a Career in Data Science
EMILY ROBINSON AND JACQUELINE NOLIS
#Data_Science
#Book
#ML
@Machine_learn
EMILY ROBINSON AND JACQUELINE NOLIS
#Data_Science
#Book
#ML
@Machine_learn
👍1
Data Science Interview (en).pdf
849.5 KB
Book: DATA SCIENCE INTERVIEW
GUIDE ACE-PREP
Authors: null
ISBN: 978-1-915002-10-5
year: 2022
pages: 136
Tags: #Data_Science
@Machine_learn
GUIDE ACE-PREP
Authors: null
ISBN: 978-1-915002-10-5
year: 2022
pages: 136
Tags: #Data_Science
@Machine_learn
👍9
https://www.globaldevelopment.dk/media/attachments/2021/07/31/practical-machine-learning-and-image-processing-1st-edition.pdf
Book: practical machine learning and image processing
year: 2019
Tags: #Data_Science #ML
@Machine_learn
Book: practical machine learning and image processing
year: 2019
Tags: #Data_Science #ML
@Machine_learn
🐼 PandaLM: ReProducible and Automated Language Model Assessment
Judge large language model, named PandaLM, which is trained to distinguish the superior model given several LLMs. PandaLM's focus extends beyond just the objective correctness of responses, which is the main focus of traditional evaluation datasets.
🖥 Github: https://github.com/weopenml/pandalm
📕 Paper: https://arxiv.org/abs/2306.05087v1
🔗 Dataset: https://github.com/tatsu-lab/stanford_alpaca#data-release
@Machine_learn
Judge large language model, named PandaLM, which is trained to distinguish the superior model given several LLMs. PandaLM's focus extends beyond just the objective correctness of responses, which is the main focus of traditional evaluation datasets.
🖥 Github: https://github.com/weopenml/pandalm
📕 Paper: https://arxiv.org/abs/2306.05087v1
🔗 Dataset: https://github.com/tatsu-lab/stanford_alpaca#data-release
@Machine_learn
❤4👍1🔥1
Intro to Python for Computer Science and Data Science 2022.pdf
49.6 MB
Book: Intro to Python® for Computer Science and Data Science
Authors: Paul Deitel • Harvey Deitel
ISBN: 1-292-36490-4
year: 2022
pages: 882
Tags:#Python #Computer_science #Data_Science
@Machine_learn
Authors: Paul Deitel • Harvey Deitel
ISBN: 1-292-36490-4
year: 2022
pages: 882
Tags:#Python #Computer_science #Data_Science
@Machine_learn
❤10👍1
Graph Data Modeling in Python.pdf
5.5 MB
Book: Graph Data Modeling in Python
Authors: Gary Hutson, Matt Jackson
ISBN: 978-1-80461-803-5
year: 2023
pages: 236
Tags:#Python #Graph #Data_Science
@Machine_learn
Authors: Gary Hutson, Matt Jackson
ISBN: 978-1-80461-803-5
year: 2023
pages: 236
Tags:#Python #Graph #Data_Science
@Machine_learn
👍14
OReilly.Training.Data.for.Machine.Learning.pdf
21.3 MB
Book: 📚Training Data for Machine Learning: Human Supervision from Annotation to Data Science (2023)
Authors: Anthony Sarkis
ISBN: null
year: 2023
pages: 332
Tags: #Machine_learning#Data
@Machine_learn
Authors: Anthony Sarkis
ISBN: null
year: 2023
pages: 332
Tags: #Machine_learning#Data
@Machine_learn
❤6👍3
Fundamentals of Data Science.pdf
12.4 MB
Book: 📚Fundamentals of Data Science Theory and Practice
Authors: Jugal K. Kalita Dhruba K. Bhattacharyya Swarup Roy
ISBN: 978-0-323-91778-0
year: 2023
pages: 336
Tags: #Data_science
@Machine_learn
Authors: Jugal K. Kalita Dhruba K. Bhattacharyya Swarup Roy
ISBN: 978-0-323-91778-0
year: 2023
pages: 336
Tags: #Data_science
@Machine_learn
🔥5❤1👍1