Designing #MachineLearning Systems โ An Iterative Process for Production-Ready Applications: http://
amzn.to/46epLSi by @chipro โ ๐ฃ๐ธ๐น๐ฒ๐ฌ๐ผ:
Engineering data and choosing the right metrics to solve a business problem Automating the process for continually developing,
@kirkdborne
-
Designing Machine Learning Systems for Production
By
–
-
Comprehensive Guide and Code for Machine Learning in Finance
By
–
Comprehensive guide to applying #MachineLearning in Finance: https://
github.com/mfrdixon/ML_Fi
nance_Codes
โฆ by Matthew F. Dixon …includes some chapters (PDF) from his book. The book: http://
amzn.to/3BHA47J
โโโโ
#AlgorithmicTrading #Fintech #ML #DataScience #Statistics #Quant #DataScientist -
Advances in Financial Machine Learning
By
–
Advances in Financial #MachineLearning: http://
amzn.to/2UXoBax by @lopezdeprado โโโโโ
#DataScience #AI #Algorithms #AlgorithmicTrading #TimeSeries #Statistics #fintech #insurtech #PredictiveAnalytics #Forecasting #AnomalyDetection #FraudDetection -
Naive Bayes classification tutorial with Python code
By
–
Naive Bayes Classification, explained with Python code: https://
github.com/taspinar/siml/
blob/master/notebooks/Naive_Bayes.ipynb
โฆ
++
Learn more in this book: http://
amzn.to/312hAHF
โโโโ
#DataScience #MachineLearning #AI #ML #Algorithms #Statistics #DataScientist #Mathematics -
Review: Mathematical Algorithms for Machine Learning
By
–
Mathematics of Machine Learning: http://
amzn.to/4eN7i52 by @TivadarDanka v/ @PacktDataML โ
Authorโs GitHub: https://
github.com/cosmic-cortex?
tab=achievements
โฆ
โ
My review: ๐ง๐ต๐ฒ ๐ฆ๐ฒ๐ ๐ข๐ณ ๐ ๐ฎ๐๐ต๐ฒ๐บ๐ฎ๐๐ถ๐ฐ๐ฎ๐น ๐๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ๐ ๐ง๐ต๐ฎ๐ ๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ฟ๐ผ๐บ ๐๐ ๐ฝ๐ฒ๐ฟ๐ถ๐ฒ๐ป๐ฐ๐ฒ This massive -
Try SciSpace Agent for Paper Discovery, Analysis, and Summaries
By
–
8/
Try @SciSpace now! Where to start? Get your own account and try these use cases for reviewing papers using the Agent: โ Discover: Find relevant papers instantly
โ Analyze: Multi-PDF with citation support + Mendeley
โ Write & Cite: Generate a structured summary
โ -
SciSpace Agent Adds Mendeley Integration for Research Workflows
By
–
6/
(3) Mendeley Integration โ Users can connect their Mendeley account to the @SciSpace Agent. As with Zotero, this integration fills the gap between reference management and research work (literature discovery, paper analysis, writing, citations, and reporting) in one research -
SciSpace launches research and Biomed AI agents within agent suite
By
–
2/
The current @SciSpace suite includes a user platform and a collection of AI tools for two major agents (supported by over 600 agents in total):
โ SciSpace Agent โ A wide-spectrum research assistant that handles end-to-end research tasks.
โ BioMed Agent โ A comprehensive AI -
Supercomputing for AI โ Foundations, Architectures, and Scaling
By
–
Supercomputing for AI โ Foundations, Architectures, and Scaling Deep Learning. [804-page masterpiece] Read it online: https://
jorditorresbcn.github.io/supercomputing
-for-ai-book/
โฆ Buy it: https://
amzn.to/4qS4pFz GitHub repo: https://
github.com/jorditorresBCN
/supercomputing-for-ai
โฆ -
Book: XGBoost for Regression and Predictive Modeling
By
–
XGBoost for Regression, Predictive Modeling, and Time Series Analysis โ Learn how to build, evaluate, & deploy predictive models: http://
amzn.to/4l2YcU9 v/ @PacktDataML โ
My review: XGBoost is definitely the focal point and central contribution of this book, along with all