forregressionanalysis,suchasridgeandlassoregression,andtheirimplementationinPython.Youwillalsolearnhowneuralnetworkscanbetrainedanddeployedformoreaccuratepredictions,andwhichPythonlibrariescanbeusedtoimplementthem.Bytheendofthisbook,youwillhavealltheknowledgeyouneedtodesign,build,anddeployenterprise-gradestatisticalmodels...
as well as its popularity in data analysis and AI applications,learning stats with the aid of the Python programming languageisan ideal approach to learning statistical concepts and putting them in practice: all at the same time!
Statistical Methods are part of the tools for analyzing securities. The following chapter explains the central limit theorem, returns, ranges, boxplots, histograms and other sets of statistical measures for the analysis of securities using Yahoo Finance API....
forregressionanalysis,suchasridgeandlassoregression,andtheirimplementationinPython.Youwillalsolearnhowneuralnetworkscanbetrainedanddeployedformoreaccuratepredictions,andwhichPythonlibrariescanbeusedtoimplementthem.Bytheendofthisbook,youwillhavealltheknowledgeyouneedtodesign,build,anddeployenterprise-gradestatisticalmodels...
Understand the different stages of a data analysis workflow Learn how you can use Python for data analysis Before you start, you should familiarize yourself with Jupyter Notebook, a popular tool for data analysis. Alternatively, JupyterLab will give you an enhanced notebook experience. You might ...
forregressionanalysis,suchasridgeandlassoregression,andtheirimplementationinPython.Youwillalsolearnhowneuralnetworkscanbetrainedanddeployedformoreaccuratepredictions,andwhichPythonlibrariescanbeusedtoimplementthem.Bytheendofthisbook,youwillhavealltheknowledgeyouneedtodesign,build,anddeployenterprise-gradestatisticalmodels...
Experience programming with Python using pandas and Matplotlib Familiarity with basic statistical concepts, linear algebra, calculus, and supervised and unsupervised learning Recommended preparation: Read “Python Infrastructure” and “Object-Oriented Programming” (chapters 2 and 6 in Python for Finance) ...
Statistical analysis and figure generation Figures were generated in Jupyter Notebooks using Python 3.7.6, Anaconda 2020.02, Conda 4.8.2, Joypy 0.2.6, Jupyterlab 1.2.6, Matplotlib 3.1.3, Matplotlib-venn 0.11.7, Numpy 1.18.1, Pandas 1.3.0, and Seaborn 0.10.0. The scatter density plots for...
Chapter 1. Gaining Early Insights from Textual Data One of the first tasks in every data analytics and machine learning project is to become familiar with the data. In fact, … - Selection from Blueprints for Text Analytics Using Python [Book]
IBM SPSS Statistics software (version 19.0, IBM Inc., Armonk, NY, USA) and Python software (version 3.6.5,Anaconda Inc.) were used for statistical analysis,where mean ± standard deviation (SD) was used for presenting and summarizing the results. For the test of agreement between manual...