Live Instructor Led Online Training Tools in Programming courses is delivered using an interactive remote desktop! .
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R Training Using Company Data
This training on R uses company data to better learn how R can be used at the company.
I. Content
There are 7 lessons in this training, and 3 problem sets to be completed after the training.
A. Lessons
During lessions, notes are reviewed and the remaining time is used to work on 3 exercises. Solutions to the exercises are handed out at the end of the session. Below times are for groups with no prior R/programming experience. (Times for groups with prior R/programming experience will be about 45 min to an hour less.)
dplyrggplot2data.table, reshape2, and stringrWatson Mini Hack Training
This project is used to support Watson training sessions at various clients conducted by IBM Developer Advocates. Because this is a public repo, it contains no client specific information. Note however that the content may be updated over time to support different training sessions. It is therefore recommended that you clone the project at the time of your training session so the material will match the agenda of your session.
Watson Services Guide for Developers
The Watson Services Guide for Developers is a summary of the information presented at the training session. It contains links to relevant information and resources and has a one page summary of each Watson API.
Labs
These are the instructions and all supporting files for the hands-on-lab exercises. The hands on lab exercises are:
Lab 1 - Watson Assistant (formerly Watson Conversation)
In this lab, you will familiarize yourself with the Watson Assistant service tooling by developing a chatbot from scratch and then extending an existing chatbot. Follow the instructions at the link below to complete the lab.
Lab 2 - Watson Visual Recognition
Datasets for Training Defensive Neural Networks
These are the Anti-Nex datasets for training deep neural networks to defend against network exploits (only web applications added so far). Under the hood these models are trained and tuned using Keras and Tensorflow. These datasets were created by merging datasets recorded from OWASP ZAP attack simulations and multi-user non-attack simulations with Django. Each model has an associated guide for preparing datasets and training models: This is a 75 MB gif I recorded while capturing the non-attack training data by running the multi-user simulation with the capture tools all active inside a single vm (note: from inside imgur, right click on the gif and select Open in video in new tab to make it larger to read the text):
Number Crunch
Number Crunch is a mental math training program. The program displays three digits with two blanks in between the digits, signifying the missing operators. To the right side of the equals sign is the result. The goal is to type in the first operator followed immediately by the second operator to satisfy the equation.
Pixy is a lightweight application for generating image datasets intended for downstream machine vision applications. With a few image labeling functions, pixy is able to achieve near human accuracy for image turking.
Pixy depends on DeepBox, pycaffe, caffe, snorkel, and vlfeat. Instructions to install each of these libraries can be found online. It is highly recommended to install these libraries on Ubuntu.
Automate installation requirements and make a user-abstracted interface
SIMON SINGS Simon Sings is a fun music and memory training game for the iPhone. Learn to sing, improve your hearing, and train your memory... at the same time! Simon plays a sequence of musical notes that you have to memorize and then repeat by singing, humming or whistling into the iPhone's microphone. With each new round the sequence becomes longer and harder to remember. Start in Beginner mode with only 3 possible notes, move up to Intermediate with 6 notes, and finally become a Maestro by mastering all 12 notes of the musical alphabet.
AdventOfCode2018
Advent of Code is an Advent calendar of small programming puzzles for a variety of skill sets and skill levels that can be solved in any programming language you like. People use them as a speed contest, interview prep, company training, university coursework, practice problems, or to challenge each other. These are my Python code examples solving the daily challenges.
TorchRecord
TorchRecord can merge the small files including images and labels into one or multiple big record file to improve the copying and reading performance. TorchRecord use LMDB as the storage database. A specific writer and loader can be used to write and read the record.
Reading Performance Benchmark
Dataset: CUB200 datasets(11788 jpg images)
Load Image and transform them to tensor (batch_size: 32)
Env: Intel(R) Xeon(R) CPU E5-2603 0 @ 1.80GHz 4core with 32 GB Mem Conventional: 100%|| 369/369 [00:42
Title
Implementation of a fully connected feed-forward neural network using the back propagation algorithm for stochastic batch gradient descent computations. Network size is adoptive and supports MLP.
Features
Activations: softmax, sigmoid
Loss functions: log-likelihood, mean-square, cross-entropy(binary equivalent of log-likelihood) Regularization: L2 Validation - Takes labels and data as input Hyper-parameters: learning-rate(eta), regularization-parameter(lambda), epochs
About
CAPTCHA22 is a toolset for building, and training, CAPTCHA cracking models using neural networks. These models can then be used to crack CAPTCHAs with a high degree of accuracy. When used in conjunction with other scripts, CAPTCHA22 gives rise to attack automation; subverting the very control that aims to stop it.
Contents
Installation
Prerequisites
Usage: How to crack CAPTCHAs
Step 1: Creating training sample data (labelling CAPTCHAs)
Step 2: Training a CAPTCHA model
Step 3: CAPTCHA Cracking
Troubleshooting
Contributing
License
Microsoft Graph training module - Microsoft Graph data connect
This module introduces you to Microsoft Graph data connect.
Lab - Using Microsoft Graph data connect to analyze to find subject matter experts
In this lab you will use Microsoft Graph data connect to analyze emails from an organization in Office 365 to find subject matter experts on specific topics.
Automate code completions tailored to your codebase with IntelliCode Team completions
With this GitHub Action, you can keep your Team completion suggestions up-to-date with your repositorys latest commit by automating the Team completions model training.
Requirements
The build agent (MSBUILD, CMAKE) has the minimum required Visual Studio version installed: For C# repositories: Visual Studio 2017 or higher For C++ repositories: Visual Studio 2019 Update 4 or higher.
Simulator
A distributed systems and infrastructure simulator for attacking and debugging Kubernetes: simulator creates a Kubernetes cluster for you in your AWS account; runs scenarios which misconfigure it and/or leave it vulnerable to compromise and trains you in mitigating against these vulnerabilities. For details on why we created this project and our ultimate goals take a look at the vision statement.
This is a set of scripts that allows for an automatic collection of tens of thousands of images for the following (loosely defined) categories to be later used for training an image classifier: Here is what each script (located under scripts directory) does. It is already ran this script for you, and its outputs are located in raw_data directory. No need to rerun unless you edit files under scripts/source_urls.
Training Noodles
A simple and powerful tool to help training multiple programs on multiple servers with only one human.
Features
Automatically deploys experiments to available servers
No need to change any existing code
Considers CPU usage, GPU usage, memory usage, disk usage, and more
Uses only SSH protocol
Relies on minimal dependencies
Allows fast prototyping
ModelZoo for Pytorch - this is a model zoo project under Pytorch. In this course, we will implement some of basic classification models which have good performance on ImageNet. Then I will train them in most fair way as possible and try my best to get SOTA model on ImageNet.
URI Online Judge Solutions
Problems solved in the URI Online Judge platform for training in programming contests.
About
These are my solutions to URI Online Judge problems. Whenever possible I will try to add more solutions to this repository. Most problems are solved in C++, but it is also possible to find solutions in Python and Haskell. The URI Online Judge is a project that is being developed by the Computer Science Department of URI University. The main goal of the project is to provide programming practice and knowledge sharing. It contains more than 1,000 problems divided in 8 big categories. This division help the users to focus on specific programming topics. All problems are available in Portuguese and English. The URI Online Judge website also has public contests on a regular basis.
Constellation Training
graph-focused data visualisation and interactive analysis application enabling data access, federation and manipulation capabilities across large and complex data sets.
Analyst Training
The Analyst Training folder contains a series of self paced exercises you can follow to become fluent with using Constellation starting with the basics of "why graphs?" in exercise 1 and move up all the way up to doing network analysis with Constellation and Python in exercise 10. Answers to exercises are also provided to verify your learning.
Exercise 1 - Why Graphs
Exercise 2 - Introduction to Constellation
Exercise 3 - Histogram View
Exercise 4 - Selecting in Constellation
Exercise 5 - Putting it Together - Checkpoint
Exercise 6 - Map View and Location Data
Exercise 7 - Conversation View and Content Data
Exercise 8 - Analytic View and Social Network Analysis
Exercise 9 - Clustering and Similarity
Exercise 10 - Network Analysis With Python If you have any feedback or have questions then feel free to submit an issue to to you. We also welcome any contribution to exercises.
Developer Training
Constellation provides significant capability out of the box, it has been designed with extensibility and modularity in mind. There are two prominent ways of extending Constellation, namely through its views or by creating plugins. Views appear as windows in the application and provide visualisation of and interaction with the graph. Plugins perform operations on the graph. In addition, there are several other ways that Constellation can be customised, including defining new attributes or even your own custom graph. This guide will introduce you to the most common ways to customise Constellation in order to solve domain-specific problems. Each chapter will introduce a new concept interspersed with a series of practical exercises. These exercises will
Experiment tracking in SageMaker Training Jobs, Processing Jobs, and Notebooks.
Overview
SageMaker Experiments is an AWS service for tracking machine learning Experiments. The SageMaker Experiments Python SDK is a high-level interface to this service that helps you track Experiment information using Python.
Experiment tracking powers the machine learning integrated development environment Amazon SageMaker Studio.
For detailed API reference please go to: Read the Docs
Concepts
For more information see Amazon SageMaker Experiments - Organize, Track, and Compare Your Machine Learning Trainings_
SwiftNNTrainier is a program for training neural networks using Apples' Metal Performance Shader library. The program allows you to define a data source, create a network topology, and test and/or train the network using that data.
A tool that executes a command on a remote machine while syncing files back and forth. The process is known as remote execution (in general) and remote build (in particular cases). Mainframer helps to move heavy operations (like compiling the source code) from a personal computer to a dedicated machine. This way you, as a developer, can use your machine for changing the source code or browsing the documentation without constant freezes and hearing jet engine-like sounds caused by the build process. The execution itself is not limited and can be applied to actions like encoding audio and video, batch processing and more. It works via pushing files to the remote machine, executing the command there and pulling results to the local machine. $ mainframer ./gradlew build Sync local remote machine... :build
All-in-one web-based development environment for machine learningGetting Started Features & Screenshots Support Report a Bug FAQ Known Issues Contribution
The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated.
Amidst is a tool to display an overview of a Minecraft world, without actually creating it. Amidst can:
Amidst was moved to a new location, since Skidoodle aka skiphs is too busy to maintain it. It has also found some new developers. One of them is DrFrankenstone, a.k.a. Treer, who is the developer of AmidstExporter. Skidoodle is still an owner of Amidst and agreed to move the project.
Free auto typer available for download. Very simple to use tool.
The Autosofted Auto Typer is a fully hotkey compatible tool, just like every other Autosofted tool. This is a FREE auto typing program and is probably our simplest program yet. All you have to do type in the message that you want repeated and then set a hotkey to start/stop the message playing.
Download the free auto mouse clicker program.
The Autosofted Mouse Clicker and Recorder is a FREE auto clicker mouse program which enables you to control where your mouse moves, when to click on something and how often to repeat the whole process. This program can be used to automate all mouse clicks.
End to end data integration and analytics platform
Pentaho tightly couples data integration with business analytics in a modern platform that brings together IT and business users to easily access, visualize and explore all data that impacts business results. Use it as a full suit or as individual components that are accessible on-premise in the cloud or on-the-go (mobile). Pentaho Kettle enables IT and developers to access and integrate data from any source, and deliver it to your business applications, all from within an intuitive and easy-to-use graphical tool.
Remove Modern UI Apps from Windows Installations or Images
Remove Modern UI (Metro) Apps from Windows. With the Windows X App Remover, you can easily read out which Apps are installed and remove the ones you do not want anymore. -News, 14th December 2015- Version 1.02 is out. Some Apps can't be removed, because Microsoft does not allow them ("System Apps"). This is now correctly handled by the program.
In the field of Tools in Programming learning from a live instructor-led and hand-on training courses would make a big difference as compared with watching a video learning materials. Participants must maintain focus and interact with the trainer for questions and concerns. In Qwikcourse, trainers and participants uses DaDesktop , a cloud desktop environment designed for instructors and students who wish to carry out interactive, hands-on training from distant physical locations.
For now, there are tremendous work opportunities for various IT fields. Most of the courses in Tools in Programming is a great source of IT learning with hands-on training and experience which could be a great contribution to your portfolio.
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