Software Programming

General Programming - Basic Git Version ControlGit is a distributed version control system which tracks changes in a set of files. Its goals include speed and efficiency, data integrity, and support for non-linear workflows. It was originally created by Linux Torvalds in 2005 for the development of the Linux Kernel. As a distributed version control system, every directory using Git is a full-fledged repository, with complete history and full version-tracking abilities, which is independent of network access or a central server. These notes rely on the ideas and learnings from the Git documentation and "Pro Git", 2nd Edition, by Scott Chacon, Ben Straub, and various other contributors. Git is free and open-source software distributed under the GPLv2.0-only licence.
General Programming - Distributed Git Workflows...
General Programming - Continuous Integration Continuous Delivery...

Data Science - Basic Approach And Process OverviewTo gain an initial understanding, an exploratory data analysis can be performed as a preliminary approach which involves interrogating, visualizing, and summarizing the main characteristics of a set of data to gain insights and identify patterns or trends. For forecasting, model can then be built using machine learning, which is a branch of artificial intelligence and computer science focussing on the use and development of data and algorithms to form a model to make prediction. Creating a model involves using a training (estimating the parameters of the machine learning method) and testing (evaluating the performance on unseen data) datasets to create an algorithm and validate the accuracy of the algorithm. ...
Data Science - IPython Interpreter And Jupyter NotebooksAs Python is an interpreted language, it is required for an interpreter to run a program by executing a single statement at a time. IPython is an interpreter designed for both interactive computing and software development, while encouraging an execute-explore workflow instead of the typical edit-compile-run workflow of other programming languages. In addition, it provides directly integrated access to the shell and filesystem of the operating system (removing the need to switch between the current session and terminal). Juypter is an initiative to design language-agnostic interactive computing tools and allows for IPython to be used as a kernel for using Python with Jupyter. With regard to data analysis, IPython and Jupyter are essential in allowing for efficient exploration, interaction, testing, debugging, and iteration. These notes rely on the ideas and learnings from the respective package documentations, "Python For Data Analysis: Data Wrangling With Pandas, NumPy, And Jupyter", 3rd Edition, by Wes McKinney (creator and developer of Pandas) in 2022, and "Python Data Science Handbook: Essential Tools For Working With Data", 2nd Edition, by Jake VanderPlas in 2022.
Data Science - NumPy Multi-Dimensional ComputationsNumPy offers the capabilities to define multi-dimensional arrays, along with a large collection of mathematical operations and algorithms to work with these arrays. The core functionality is its data structure and methods for manipulation, which act as an efficient and flexible container to be utilized when analysing data sets. Various packages build on the functionality of NumPy for applications in specialized domains, such as Pandas and Statsmodels for data analysis, TensorFlow and PyTorch for deep learning, and OpenCV for image processing. These notes rely on the ideas and learnings from the respective package documentations, "Python For Data Analysis: Data Wrangling With Pandas, NumPy, And Jupyter", 3rd Edition, by Wes McKinney (creator and developer of Pandas) in 2022, and "Python Data Science Handbook: Essential Tools For Working With Data", 2nd Edition, by Jake VanderPlas in 2022.
Data Science - Pandas Exploratory Data AnalysisData analysis is the process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information and informing conclusions to support decision-making. This involves applying inferential statistical analyses and creating visualizations in order to interpret the results and summarize the main characteristics of the data. The typical information and conclusions extracted from the data include interactions, patterns, and anomalies. These notes rely on the ideas and learnings from the respective package documentations, "Python For Data Analysis: Data Wrangling With Pandas, NumPy, And Jupyter", 3rd Edition, by Wes McKinney (creator and developer of Pandas) in 2022, and "Python Data Science Handbook: Essential Tools For Working With Data", 2nd Edition, by Jake VanderPlas in 2022.
Data Science - Data Visualization Approaches...
Data Science - Using Python For Data Science...

Database Management - Structured Query Language With PostgreSQLStructured Query Language (SQL) is a standard language described by ISO/IEC 9075 for creating and working with databases stored in a set of tables. The actual implementations through database management systems use this standard language and usually add their own extensions for additional specifications. The most common implementations include PostgreSQL, MySQL, Microsoft SQL Server, Oracle Database, and SQLite, where PostgreSQL will be used as a reference, since it is a popular, versatile, and open source database (although most core functionality is shared). These notes rely on the ideas and learnings from the respective package documentations and "SQL For Data Analysis: Advanced Techniques For Transforming Data Into Insights", 1st Edition, by Cathy Tanimura in 2021.

Website Development - Eleventy Initial SetupEleventy is a static site generator and was created to be a JavaScript alternative to Jekyll. It offers a simple and minimal configuration, as well as the possibility for advanced customization options. It is also designed to work with an existing directory structure and can use multiple independent template engines, which aims to decouple the content from the static site generator and avoid holding the content hostage to the static site generator - although this is the intention of the project, these notes still avoid the specialized features and focus on uses which are generalized to always ensure the content is independent and transferable. The project was started and is maintained by Zach Leatherman.
Website Development - Eleventy CustomizationsIt is possible to extend the functionality of Eleventy through ... , while also employing other Node packages from the configuration file. This include the inclusion of using Syntactically Awesome Style Sheets (SASS), performing minification of ...text... file, creating a robots exclusion protocol, and creating a sitemap. Although primarily focussed on Eleventy, some of the other concepts, like may be applicable to web development in general.

Hardware And Electronics

Engineering And Physics

Mathematics And Statistics

Miscellaneous Notes

Finances And Investing - Understanding Capital MarketsWhen studying markets, it is necessary to explore and understand their basic workings. These notes are based on ideas which were collected while learning about finances and investing. A focus is applied to the Efficient Market Hypothesis and underlying relationship between risk and return. Other points are discussed, such as the irrationality of selecting individual securities or trying to time the market based on forecasts due to the arithmetic of active management. The underlying research was recognized and uncovered with contributions from Louis Bachelier, Paul Samuelson, William Sharpe, and Eugene Fama with many additions from other proponents. As initially observed by Louis Bachelier in 1900, "past, present, and even discounted future events are reflected in market prices, but often show no apparent relation to price changes" (as would be expected if the current price of a security is related to currently available information and changes in the current price of the security are only related to the unexpected outcomes of future events).
Finances And Investing - Money Theory Definitions...
Finances And Investing - Psychology Of MoneyThese notes are primarily based on the ideas and learnings from "The Psychology Of Money: Timeless Lessons On Wealth, Greed, And Happiness", 1st Edition, by Morgan Housel in 2020. The description of the book mentions: "Money - investing, personal finance, and business decisions - is typically taught as a math-based field, where data and formulas tell us exactly what to do, but in the real world people do not make financial decisions on a spreadsheet, but rather they make them at the dinner table or in a meeting room, where personal history, your own unique view of the world, ego, pride, marketing, and odd incentives are scrambled together". The author shares short stories which explore the strange ways people think about money. Overall, the premise of the book is made clear from the beginning and can be summarized as "doing well with money has a little to do with how smart you are and a lot to do with how you behave". There is some subjectivity with regard to some of the presented ideas, such as the critic of the idea of diversification across time from Barry Nalebuff and Ian Ayres. Other concepts, many of which are often neglected, are presented for further thought and consideration.
Finances And Investing - An Efficient Market StoryAn investment increases in value, as there is an expected return resulting from a compensated risk. In an efficient market and when properly measured, this relationship between expected return and risk is expected to be proportional, where it is assumed that the current valuations within the market are already correct for bonds, equities, commodities, or any other asset based on their expected future valuations. It is possible to systematically identify factors in order to target a certain level of risk, although this will result in a reduction of diversification.
Finances And Investing - Guide To Factor-Based InvestingThese notes are primarily based on the ideas and learnings from "Your Complete Guide To Factor-Based Investing, The Way Smart Money Invests Today", 1st Edition, by Andrew Berkin and Larry Swedroe in 2016. The description of the book mentions: "There are hundreds of exhibits in the investment factor zoo, so it is difficult to see which ones are actually worth time and money. This brings a thorough yet still jargon-free and accessible guide to applying the most valuable quantitative and evidence-based approaches to outperforming the market: factor investing - a journey through the land of academic research and an extensive review of its quest to uncover the secret of successful investing". The authors describe unique criteria and characteristics in the definition of a factor as persistent, pervasive, robust, investible and intuitive. Overall, the premise of the book is structured to remain objective and provide reputable evidence for all the claims put forward with citations for further reference.
Finances And Investing - Additional Factor-Based InvestingThese notes are a continuation of the notes primarily based on the ideas and leanings from "Your Complete Guide To Factor-Based Investing, The Way Smart Money Invests Today", 1st Edition, by Andrew Berkin and Larry Swedroe in 2016. Other additional considerations are presented, such as reasonable expectations around the performance of factors in the future and expanded definitions of several factors. Moreover, as with the factors which were previously mentioned for equities, asset pricing models have been created using factors which are relevant to the relationship of risk within bonds. As before, there needs to be the establishment of unique criteria and characteristics in the definition of a factor as persistent, pervasive, robust, investible and intuitive. Other miscellaneous points are further considered.
Finances And Investing - Lifecycle Investing Across TimeThese notes are primarily based on the ideas and learnings from "Lifecycle Investing: A New, Safe, And Audacious Way To Improve Performance Of Retirement Portfolios", 1st Edition, by Ian Ayres and Barry Nalebuff in 2010. The description of the book mentions: "Diversification provides a well-known way of getting a free lunch, where, by spreading money across different kinds of investments, investors can earn the same return with lower risk (or a much higher return for the same amount of risk). There is an additional form of diversification which can be considered for an investor to diversify their portfolio over time. By using leveraging when young, investors can substantially reduce overall risk while improving their returns". There is clear evidence to the proposed strategy, although there are also possible concerns around real implementation, and it is as spectacular as learning about the Efficient Market Hypothesis.
Finances And Investing - Understanding Margin RequirementsWhen implementing strategies for mutliple periods, it can be useful to consider leverage in margin accounts, where the leverage is accessed through a margin loan from the broker. With most brokers, a margin loan is available through Regulation T Margin for most investors or Portfolio Margin above a certain net worth. The potential benefits of using leverage are explored through lifecycle investing and, if used correctly, present the opportunity to decrease the overall risk during accumulation. As an alternative to margin loans, box spreads are mentioned which make it possible to borrow directly from the market instead of a broker. However, it is a perfectly acceptable and rational choice to avoid the possible disaster from leverage and simply perform regular contributions without further complications.
Finances And Investing - Safe Withdrawal Rates...
Finances And Investing - Financial Analysis IntroductionFinancial analysis is related the evaluation of the financial capacity and suitability of a business and potential opportunities. This involves considering types of accounting and various accounting principles with an importance placed on the income statement, balance sheet, and cash flow statement with regard to an overall business and its projects, budgets, and other related transactions. The insights gained from these documents provide an indication of the financial state of a business and areas in which it may be struggling or excelling. In addition, an indication of performance can be calculated based on various metrics with regard to whether the business is stable, solvent, liquid, and profitability, such that these metrics can be compared against other similar businesses or historic performance. From a broad perspective, financial analysis is used to evaluate economic trends, set financial policy, build long-term plans for economic activity, and identify projects for investment. These notes were compiled while completing a basic course on financial analysis.