Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022
Die Hauptfunktionen von jacopotagliabue/mlsys-nyu-2022 sind: Data Processing and Analysis, Data Science Tooling, Educational Resources, Training Resources.
Open-Source-Alternativen zu jacopotagliabue/mlsys-nyu-2022 sind unter anderem: jadianes/data-science-your-way — Ways of doing Data Science Engineering and Machine Learning in R and Python. kevinschaich/pyspark-cheatsheet — 🐍 Quick reference guide to common patterns & functions in PySpark. datasciencespecialization/courses — This project is a data science curriculum and instructional syllabus designed to teach the fundamental principles and… handcraftsman/geneticalgorithmswithpython — source code from the book Genetic Algorithms with Python by Clinton Sheppard. jinglescode/python-signal-processing — splearn: package for signal processing and machine learning with Python. Contains tutorials on understanding and… khangich/machine-learning-interview — This project is a curated collection of technical reference materials and study guides designed for machine learning…
source code from the book Genetic Algorithms with Python by Clinton Sheppard
Ways of doing Data Science Engineering and Machine Learning in R and Python
This project is a data science curriculum and instructional syllabus designed to teach the fundamental principles and tools of the field. It provides a structured set of learning materials, including R programming courseware and guides for statistical learning. The materials focus on the practical application of data science, covering data cleaning, visualization, and exploratory data analysis. It includes resources for mastering specific techniques such as linear regression, classification, and unsupervised learning. The curriculum is organized into a modular sequence of educational modules
splearn: package for signal processing and machine learning with Python. Contains tutorials on understanding and applying signal processing.