Search Results for "dynamicreports-examples" - Page 2
Sort By:
Showing 39 open source projects for "dynamicreports-examples"
View related business solutions-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
-
1
Python Tutorials
Machine Learning Tutorials
Python Tutorials is a large set of educational tutorials focused on Python and related technologies, catering especially to learners who want hands-on examples and clear explanations. Created by an experienced instructor and educator, the repository covers a wide range of programming basics and advanced topics. This includes foundational Python concepts, data processing with libraries like NumPy and pandas, threading and multiprocessing for concurrency, and practical use of libraries such as Matplotlib for data visualization. ... -
2
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
...Each section includes runnable code examples that progressively increase in complexity, helping learners build intuition while practicing hands-on implementation. Because the tutorials are concise and practical, the project is widely used in classrooms and self-study environments. Overall, it functions as both a learning curriculum and a quick reference for common PyTorch workflows. -
3
Tensorflow and deep learning
A crash course in six episodes for software developers
Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights, biases, activation functions, and gradient descent, as well as more advanced techniques like convolutional networks, recurrent networks, and reinforcement learning. ... -
4
Think Bayes
Code repository for Think Bayes
...Instead of heavy focus on continuous mathematics or calculus, the book emphasizes learning Bayesian inference by writing Python programs. The project includes code examples, scripts, and environments that correspond to the chapters of the book. Learners can run the code, experiment with probability distributions, compute posterior probabilities, and understand Bayesian updating via simulation and algorithmic methods. The book and code encourage thinking in terms of discrete approximations (sums over distributions) rather than continuous integrals, making it more accessible to many programmers. ... -
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
-
5
BPF Performance Tools
Official repository for the BPF Performance Tools book
BPF Performance Tools Book is the companion repository for Brendan Gregg’s book on Linux performance analysis using eBPF and BCC tracing technologies. The project contains scripts, examples, and reference material that demonstrate how to inspect kernel behavior, application performance, CPU usage, networking activity, file systems, and system bottlenecks in real time. It serves as both an educational resource and a practical toolkit for Linux engineers, SREs, and performance analysts working with modern observability workflows. ... -
6
Pydicom by examples
Basic and intermediate examples of DICOM library with Jupyter
Basic and intermediate examples to read, modify and write DICOM files with Python code using Jupyter - To install Jupyter - https://jupyter.org/install ====== All examples are based on Pydicom. An open source library - https://pydicom.github.io/ -
7
Computer Glossary
is a rich dictionary containing multiple computer-related terms
...The program comes with a simple interface and lets you easily search any term. The results will let you see the word's definition, references to other related terms in the dictionary, examples, and the source of the information. -
8
Learn Python the Hard Way
Concise study notes derived from “Learn Python the Hard Way”
...The material favors clarity over abstraction, keeping examples runnable and easy to modify in any editor. It works well as a companion to more exhaustive books, giving you a lightweight way to drill fundamentals and build muscle memory. -
9
stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course
This repository contains code examples for the course CS 20: TensorFlow for Deep Learning Research. It will be updated as the class progresses. Detailed syllabus and lecture notes can be found in the site. For this course, I use python3.6 and TensorFlow 1.4.1. -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
10
Logicheck
An interactive tool to test logical structures and expressions
...A truth table can then be generated for any such set of expressions. It can also be used to test the validity of deductive arguments - the program will advise whether an argument is valid and if not, list the counter examples to the argument. -
11
Matplotlib tutorial
Matplotlib tutorial for beginner
...It provides a sequence of example scripts and notebooks that cover fundamental plotting tasks: line graphs, histograms, scatter plots, bar charts, customizing axes, labels, legends, and styling. This makes it ideal for someone learning data analysis or exploratory data visualization for the first time and needing concrete, runnable examples rather than abstract explanations. As the tutorial builds progressively, learners can gradually advance from simple static plots to more complex visualizations, learning how to control figure size, add multiple subplots, adjust plot aesthetics, and handle different data types. Because it is code-first, users can copy, modify, and run the examples on their own datasets, encouraging experimentation and deepening understanding. -
12
simplex with branch and bound
A tool for teaching simplex and branch & bound methods
This is a tool for teaching simplex and branch & bound methods. For simplex method, it comes with several examples including degeneracy and cycling, and allow the user to dictate how to pivot. For branch and bound method, it is desinged to interact with the user to explore all possible branch and bound trees. The user can also load a problem from a text file or simply type in a model directly. The format is very simple and very similar to the LP format, see the packed-in examples. -
13
VisualRiSC
Toolbox visualizing computations of Realizable Sign Conditions.
...VisualRiSC provides implementations of such notions and functions using the Python package SymPy, on the one hand, and an interface to Gnuplot in order for a visualization of examples using the Python package Gnuplot.py. -
14
Notejam
The easy way to learn web frameworks
...The easy way to start with a new framework is to compare it with frameworks you already know. The goal of the project is to help developers easily learn new frameworks by examples. Notejam is a unified sample web application (more than just "Hello World") implemented using different server-side frameworks. Currently python, php, ruby and javascript frameworks are supported. Currently project is hosted on GitHub http://github.com/komarserjio/notejam