#Python for #Finance Cookbook — 50+ Recipes for Applying Python to Financial Data Analysis: http://
amzn.to/3QMD4Fw from @PacktPublishing ————
#Coding #DataScience #DataScientists #DataLiteracy #MachineLearning #DeepLearning #TimeSeries #PredictiveAnalytics #Forecasting #fintech
RESEARCH
-
Python Finance Cookbook: 50+ Recipes for Financial Data Analysis
By
–
-
Quantum Machine Learning and Optimization in Finance Book
By
–
Get future-ready with this book from @PacktPublishing >> "Quantum #MachineLearning and Optimization in #Finance" (391 pages): http://
amzn.to/3g9vkh1
———
#BigData #DataScience #NeuralNetworks #AI #ML #ORMS #QuantumComputing #ComputationalScience #fintech -
Data Science Applications in Economics and Finance with Advanced Analytics
By
–
#DataScience for #Economics and #Finance — Methodologies & Applications: http://
amzn.to/2UbaBhs
————
#BigData #Analytics #fintech #AnomalyDetection #PredictiveAnalytics #PredictiveModeling #MachineLearning #AI #PrescriptiveAnalytics -
Implemented Neural Networks Projects and Applied Machine Learning Repository
By
–
Implemented #NeuralNetworks Projects: https://
medium.com/coders-mojo/im
plemented-neural-networks-projects-d25a6476d72b
… compiled by @NainaChaturved8 ————
#DataScience #DataScientists #AI #Coding #Python #MachineLearning #DeepLearning ————
Also see below the repository of 60+ implemented Applied ML Projects with code… -
Data Preprocessing: The Foundation of Data Science Solutions
By
–
#Data preprocessing –The foundation of #DataScience solution
by Shehryar Mallick @DataScienceDojo Read more: https://
buff.ly/47Tuf2h #DataScientists #ArtificialIntelligence #MI #MachineLearning cc: @pascal_bornet @yvesmulkers @kuriharan -
Computing Requirements for Simulating Human Brain Functions
By
–
The number of brains to simulate an H100 is also inconveivable. A more interesting question: how much compute is necessary to simulate perception, motivation, planning and reflection of a person?
-
Brain Learning Mechanisms Mirror Computational Models
By
–
The brain may learn about the world the same way some computational models do
by Anne Trafton @MIT Read more: https://
buff.ly/49rILjc #BigData #MachineLearning #ML #MI #DataScience cc: @pbalakrishnarao @bigdata @rtehrani -
Evaluating AI Outputs: Subjective Preferences and Domain Expertise
By
–
Subjective: depends on the use-case… sometimes I’ll just go with my preference, or ask a few people to rate outputs. Domain specific: ask smarter LLMs or domain experts!
-
AI Models Learn Faster With Less Training Data
By
–
Doubt it. As models get smarter, less data will be needed to teach them new things. So if today, it takes millions of examples to teach it a new language, a couple years from now, it may only need a few thousand.
-
Adding Example Inputs Outputs Improves Prompt Performance
By
–
Try adding example inputs/outputs to the prompt!