Password guessing tools (HashCat and John the Ripper) enable users to check millions, even billions of passwords per second against password hashes. When a password is “hashed”, it is turned into a scrambled representation of itself. A user’s password is taken and the hash value is derived from a combination of the given password and a key known to the site or service. Password guessing tools make it easy to identify weak passwords when stored in this hash form. The effectiveness of the guessing software relies on its ability to test large numbers of highly likely passwords against each password…
Maximum Likelihood Estimate (MLE) primarily deals with using parameter inference to determine which parameters maximize the probability of data. This calculated parameter can be used to help you predict the outcome of future experiments.
A few relevant terms:
Conditional probabilities are values that we use all the time in data science. The…
The structure of this article is as follows:
If you’re here strictly for the tutorial, navigate down to the Steps we’ll follow section.
The “Google Stack” is becoming exceedingly popular amongst non-technical teams who need to share and analyze their data. Today we’ll learn how to leverage BigQuery and Google Data Studio to store, transform, visualize, and share our data in a cloud environment.
The process of piping data through the Google atmosphere can be a pain to get up and running. …
If you’re already familiar with the concepts of testing and terminology as it relates to software, absolutely skip ahead to a more relevant section
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Please note: To get the most out of the following material you would ideally have some OOP experience in Python, some basic knowledge of HTML elements and their uses, and a basic understanding of the Dash framework (use of
layout and components). If you are unfamiliar with the Dash basics, you can check out Dash 101 for a complete walkthrough.
Inputto update an
Dropdownoptions to update the contents of a
Please note: In order to get the most out of the following material before beginning this article, you would ideally have some OOP experience in Python, some knowledge of HTML elements and their functions, and some interesting data (the data I provide here is rather boring).
Dash is a (mostly) open-source framework built by Plotly and used for creating analytics-centric web applications in Python. Dash — built on top of Plotly.js, React.js, and Flask — allows you to create and deploy high-quality, highly customizable dashboards and interfaces for displaying and exploring data.
In this episode of SQL Crash Course, we’re going to learn how to combine multiple tables in SQL, and maximize the efficacy of our
SELECT statements using a
JOIN clause. We’re going to learn about the 4 different types of
JOIN methods and when we might want to use each one. We’re finally going to wrap up by creating a database and some tables, adding some data, and trying to implement some
This is episode 3 of this SQL Crash Course series. If you’re unfamiliar with SQL concepts like pulling data, creating tables, adding and deleting rows, etc…
In this installment of SQL Crash Course, we’re going to learn the difference between a SQL database and a SQL table, and how to create them both — we’re going to get a more complete look at SQL and SQLite data types in the process. We’re then going to learn how we can add and delete data from these tables, and how we can manage the tables within a database.
This is episode 2 of our SQL Crash Course series. The last article talked about what SQL is, why it’s useful, and how we can use it to select and…
We’re going to learn what SQL is, what we can use it for, and then we’re going to start writing some basic queries for selecting and filtering data from a database.
Note: We won’t actually be working with a SQL database today, we will be using Python to create a dataframe and then will use a library called pandasql to query it. If you are unfamiliar with Python, I still suggest you following the tutorial and paying attention to the SQL commands and their outputs.
Data is everywhere, and more of it is being created every minute. We used to…