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Edgecate
Приєднався 2 лип 2018
Easy Knime Tutorial! Learn the interface & create a workflow!
This tutorial is sampled from my full course on Udemy (50% Sale Now!): www.udemy.com/course/learn-knime-fast/?couponCode=KNIMETIME
Tutorial file: docs.google.com/spreadsheets/d/1X6M19_oZqNY2ARg3EKV0GqLZcXVmq6DF/edit?usp=drive_link&ouid=116654360430272691932&rtpof=true&sd=true
00:00 Intro
00:21 Course Outline
3:08 Download & Install Knime
5:03 Interface Tour
5:17 Knime Explorer
5:45 Workflow Editor / Canvas
6:15 Node Repository
8:16 Workflow Coach
9:03 Outline, Console, Description Window
9:14 Console
9:23 Description Window
9:47 Interface Tour End
10:15 Excel Reader Configuration Window
14:28 Row Filter Configuration Window
14:51 Excel Writer Configuration Window
In this beginner-friendly course, you're going to learn how to use - in my opinion - the best Robotic Process Automation tool on the market - Knime!
Course Outline
-Install Knime & learn to navigate the interface
-Solve 3 real world IT case studies with Knime, whilst showing you how to use the program at the same time
Case Study 1: Automate a Supermarket Sales Report
You’re going to create a workflow that automatically calculates the Profit for each Supermarket item based on Accounting data. You'll data cleanse the Aisle name, aggregate the results into a pivot table, and create some pretty charts for middle management that like to look at colourful pictures.
By solving this case study, you’ll learn how to use Knime to:
Read Excel files
Remove duplicates
Do an Inner & Left Join
Filter rows
Round numbers
Transform arithmetic, string, and conditional values
Create a pivot table
Do basic visualisation, and
Export to Excel
Case Study 2: Splitting & joining a HR report about Employee Cost
HR have a file that contains all employees in the company.
HR has asked you to split this file for them by Department so they can then email it to each Department Head and ask them to forecast the salary cost of each of their employees.
When the Department Heads have filled it in and emailed it back, HR wants you to combine all the forecasts back together into 1 file.
By doing this case study, you'll learn how to do the following in Knime:
Read Excel files
Use a Group By Loop
Use Flow Variables, and
Export to Excel
Case Study 3: Bitcoin arbitrage
Arbitrage is taking advantage of price differences of an asset. For example, Bitcoin might cost $25000 one exchange, and $30000 on another. Therefore, a price difference of $5000.
Arbitrage is buying Bitcoin on the cheaper exchange, and transferring to and selling it on the expensive exchange.
We’ll be using Knime to look up 3 Crypto Exchanges to get the price of Bitcoin against the USD, and identify if there’s any arbitrage opportunities.
Keep in mind, you won't make any money from doing this - you're like, 10 years too late where the price differences between exchanges used to be huge. This is really for educational purposes only. It's not financial advice, and don't be silly with your money.
By doing this case study, you'll learn how to do the following in Knime:
Use Flow variables
Create a GET API Request
Parse JSON To Table
Filter Columns
Transform string, and
Use Metanodes to tidy up a busy workflow
Tutorial file: docs.google.com/spreadsheets/d/1X6M19_oZqNY2ARg3EKV0GqLZcXVmq6DF/edit?usp=drive_link&ouid=116654360430272691932&rtpof=true&sd=true
00:00 Intro
00:21 Course Outline
3:08 Download & Install Knime
5:03 Interface Tour
5:17 Knime Explorer
5:45 Workflow Editor / Canvas
6:15 Node Repository
8:16 Workflow Coach
9:03 Outline, Console, Description Window
9:14 Console
9:23 Description Window
9:47 Interface Tour End
10:15 Excel Reader Configuration Window
14:28 Row Filter Configuration Window
14:51 Excel Writer Configuration Window
In this beginner-friendly course, you're going to learn how to use - in my opinion - the best Robotic Process Automation tool on the market - Knime!
Course Outline
-Install Knime & learn to navigate the interface
-Solve 3 real world IT case studies with Knime, whilst showing you how to use the program at the same time
Case Study 1: Automate a Supermarket Sales Report
You’re going to create a workflow that automatically calculates the Profit for each Supermarket item based on Accounting data. You'll data cleanse the Aisle name, aggregate the results into a pivot table, and create some pretty charts for middle management that like to look at colourful pictures.
By solving this case study, you’ll learn how to use Knime to:
Read Excel files
Remove duplicates
Do an Inner & Left Join
Filter rows
Round numbers
Transform arithmetic, string, and conditional values
Create a pivot table
Do basic visualisation, and
Export to Excel
Case Study 2: Splitting & joining a HR report about Employee Cost
HR have a file that contains all employees in the company.
HR has asked you to split this file for them by Department so they can then email it to each Department Head and ask them to forecast the salary cost of each of their employees.
When the Department Heads have filled it in and emailed it back, HR wants you to combine all the forecasts back together into 1 file.
By doing this case study, you'll learn how to do the following in Knime:
Read Excel files
Use a Group By Loop
Use Flow Variables, and
Export to Excel
Case Study 3: Bitcoin arbitrage
Arbitrage is taking advantage of price differences of an asset. For example, Bitcoin might cost $25000 one exchange, and $30000 on another. Therefore, a price difference of $5000.
Arbitrage is buying Bitcoin on the cheaper exchange, and transferring to and selling it on the expensive exchange.
We’ll be using Knime to look up 3 Crypto Exchanges to get the price of Bitcoin against the USD, and identify if there’s any arbitrage opportunities.
Keep in mind, you won't make any money from doing this - you're like, 10 years too late where the price differences between exchanges used to be huge. This is really for educational purposes only. It's not financial advice, and don't be silly with your money.
By doing this case study, you'll learn how to do the following in Knime:
Use Flow variables
Create a GET API Request
Parse JSON To Table
Filter Columns
Transform string, and
Use Metanodes to tidy up a busy workflow
Переглядів: 184
Відео
Data Cleaning In Python Pandas (Beginners Data Analyst Tutorial)
Переглядів 554Рік тому
Data Cleaning In Python Pandas (Beginners Data Analyst Tutorial) Course Files here: github.com/edgecate/Data-Analyst-Pandas-Tutorial In this video, you'll learn the basics of a Python library I used a lot in my data projects to do ETL, data cleansing, and report automation. It’s called Pandas and it’s like a smarter, musclier, and cuter version of Excel VBA and SQL. You can use Pandas to query ...
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Переглядів 840Рік тому
Animate Like South Park With Adobe Character Animator! A Worldwide Privacy Tour tutorial on how to draw and animate Prince Waaagh (Prince Harry) from South Park. I found a good reference image of Prince Waaagh and traced over him in Adobe Illustrator, recorded the audio in Audacity, animated it Adobe Character Animator, and compiled it in Adobe After Effects. You ever heard of a thing called PR...
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Переглядів 798Рік тому
Learn how to easily animate yourself with basic motion capture & automated lip syncing - an easy animation tutorial with zero animation experience required! We'll learn how to use: ✅ Adobe Illustrator to draw yourself ✅ Adobe Character Animator to animate yourself with motion capture & automated lip syncing, and ✅ Adobe After Effects to edit, compile, and export your video You can use this tuto...
DIY Custom Object Detection Model via Transfer Learning (Tensorflow Lite Edge TPU)
Переглядів 5 тис.2 роки тому
A tutorial on how to create your own Tensorflow Lite custom object detection model via transfer learning for Edge TPU devices like the Google Coral and Asus Tinker Edge T. We'll use this website as a guide: coral.ai/docs/edgetpu/retrain-detection/ Chapters: 0:16 Install Docker 1:19 Clone Google Coral Tutorials repo 1:53 Start the Google Coral Tutorials Docker Container 2:11 Download Google's Tr...
[Python ANPR Course] Real-Time Automatic Number Plate Recognition In Your Car!
Переглядів 43 тис.2 роки тому
A tutorial on how to code a real-time Automatic Number Plate Recognition (ANPR) system that you can install in your vehicle! You'll basically be a highway patrol police car! This is a 56 minute Python course on how to develop an Automatic License Plate Recognition (ALPR) system using the Asus Tinker Edge T with Python 3. Source code here: github.com/edgecate/ANAL You'll learn how to: ✅ Use a De...
Asus Tinker Edge T - Install Jupyter Notebook
Переглядів 5942 роки тому
Tutorial: How to install Jupyter Notebook on the Asus Tinker Edge T (ATET). With a proper Python code editor in Jupyter, you can now comfortably code on your Tinker Edge T without having to use a text editor like nano which is frustrating to use for coding. Asus Tinker Edge T spec sheet: CPU: Asus Tinker Edge T SoC 1.5GHz Quad Core Cpu (NXP i.MX 8M) RAM: 1GB LPDDR4 GPU: GC7000 Lite TPU: Google ...
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Asus Tinker Edge T - Build OpenALPR From Source
Переглядів 1,2 тис.2 роки тому
Tutorial: How to install OpenALPR from Source on the Asus Tinker Edge T (ATET). OpenALPR is an awesome library if you want to specifically convert license plates to text when Tesseract OCR might struggle to do so. We'll be following the steps in this link: github.com/openalpr/openalpr/wiki/Compilation-instructions-(Ubuntu-Linux) We're using "The Easy Way" method because the Python bindings from...
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Переглядів 5372 роки тому
Tutorial: How to install Tesseract OCR from Pre-Built Binaries, and how to Build Tesseract OCR From Source on the Asus Tinker Edge T (ATET). Installing Tesseract OCR from Pre-Built Binaries gives you access to version 4, but building Tesseract from source gives you access to the latest version (v5 at the time of recording). If you only need v4, then save yourself the hassle and get the pre-buil...
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Переглядів 1,4 тис.2 роки тому
Tutorial: How to install OpenCV from Pre-Built Binaries, and how to Build OpenCV From Source on the Asus Tinker Edge T (ATET). Building OpenCV from Pre-Built Binaries gives you access to OpenCV version 3, but building OpenCV from source gives you access to the latest version (v5 at the time of recording). If you only need v3, then save yourself the hassle and get the pre-built binaries. Otherwi...
Python For Accountants 2023 | Introduction
Переглядів 6 тис.2 роки тому
Welcome to Python For Accountants 2023! Course Link: www.udemy.com/course/python-for-accountants/?referralCode=B73C1764B5B44F604F72 Course Files: github.com/edgecate/Python-For-Accountants This is a 3 hour Beginners Python Accounting Course that covers: Chapter 1: ✔ Introduction & Course Outline Chapter 2: ✔ Python Fundamentals & Syntax ✔ Case Study | Automated Stock Market Analysis with the YF...
Asus Tinker Edge T - Object Detection Inference Server Tutorial
Переглядів 1,7 тис.3 роки тому
Tutorial: How to setup an Object Detection Inference Server on the Asus Tinker Edge T (ATET). This will allow any device to connect to the ATET and view its webcam whilst running an Object Detection model. First off, open your Router settings and enable port 4664 for your Asus Tinker Edge T. Then in Mendel Linux, type the following into your weston-terminal: cd home/mendel/examples-camera/all_m...
Asus Tinker Edge T - Object Detection Tutorial (opencv, gstreamer)
Переглядів 3,7 тис.3 роки тому
Tutorial: How to perform Object Detection Inference on the Asus Tinker Edge T (ATET). Download the Google Coral Github which contains example Inference code for gstreamer, opencv, pygame, and raspicam. This video covers opencv and gstreamer. Upon booting into Mendel Linux, open a weston-terminal and install Git: sudo apt-get install git Then clone the Google Coral Github: sudo git clone github....
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Переглядів 8093 роки тому
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okx and bitforex APIs not working
can you take the data from coinmarketcap and make a video or file comparing the prices?
Or in the file be used?
Can image in the phone be used?
Thank you
Better than ChatGPT! Thankyou - many hours saved I suspect
My first try with Character Animator : ua-cam.com/video/YvKghEeQKrQ/v-deo.html
Impressive!! Well done!
Please make a video on how to do this
Nice one mate!!
i have a flashed tinker r board could u please help me start using it when I power it on it is recognized by my ubuntu machine as 2 mounted storage volumes how should I proceed
You are an exceptional teacher, Andrew! I noticed you have not uploaded on here in a while. Do you have a new channel? If so, please let us know! Cheers, Eileen
Super useful, thank you!
I LOVE ANAL
wow
this is the best explanation and new skill unlocked . thank you very much
Thanks mate
ANAL? 💀💀☠️☠️
you shoud make ANAL HAZ then you can read hazmat plates as well
Great work 👏👏
Thank youuuuuuu🧡🧡🧡
我要買硬體
Did you make the code public?
Hello, first of all, thank you for all the information and dedication you share on your excellent channel. I want to ask you what you recommend to make an application for the detection and recognition of Car License Plates/License Plates/Patents (ANPR) of a WEB camera or a standard video surveillance camera for a development board of medium capacity but in real time such as to give access to cars at a door or barrier (night lighting may be adequate). With the following options and know which one you recommend (if you have any other, welcome the suggestion) - Development board: Raspberry Pi, Google Coral, ASUS Thinker Edge, Jetson Nano, etc. - Programming Language: Python, C++, Java, .Net, Nod.js, etc. - Libraries and/or Framework / tools: Yolo, OpenCV, OCR, preferably not Cloud - To train the model that you would recommend, or if there is already one that can be purchased for my case - I am in Mexico and the license plates would only be from the country
is it possible to use ipcam insted an analog cam
Why tf do you have such low sub count? Most of your content seems great!
The only thing you’re missing is an IR filter and an IR Illuminating device of the same NM basically it reflects back only IR lighting into the cam and the computer can’t actually see the car it can only see the plate and outline of text
The mdt isn't supported in windows 11 anymore you have to use something else the newer Management Console. Connecting to the Tinker usb type c port The Tinker will act as a DHCP server. From the Tinker console type command ifconfig and you will see it's IP. On Windows 11 machine, It creates a NDIS network adapter device with an IP in the same range as the Tinker. Go to your network and make sure this NDIS remote connection is enabled if it isn't already. Ping each other and check. So now you can SSH, Putty or, share a network drive as you are connected on the same local network directly through the NDIS. Well...long enough to setup a superuser and secure SSH tunnel with pub/priv keys and use Wifi instead of NDIS.
Great video, quick question, how did you get the model? did you train it or it's a pretrained model? thanks
could you tell me about what should i do for,,when i create user in django,,user should be created automatically in xero app too??
I'm doing your Skillshare class, so far so good (on episode 38). You mention we can download the character to follow along, and it's not there. Can you link to the file? Thx!
omg you are a god! You saved me !
Thank you soooo much. It was really helpful. God bless you. ❤
@Edgecate First of all thank you for making this tutorial it`s a life saver for me. However I have doubt regarding the response.url like can we automate conset approval here. As we manually have to go to the approval page and click "Alllow for 30 minutes". Please let me know if there`s a way. Thanks you in advance!
I've heard ANPR, ALPR and LPR but never ANAL. Thanks for the giggle
Great content .. keep going 👍🏾
How to use a normal Interface like windows and Can i install other Os like android on it?
Good, but the column date has different formats and some are text and others numbers ,how i can fixed?
Hi, what a great tutorial, man!!! But I have one issue. I have followed all steps of your tutorial and at the end when i type: python3 detect.py to run the detection script, it shows: Loading ../all_models/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite with ../all_models/coco_labels.txt labels. (that seems to be same with you) but instead of cam detection screen appeared, it is written in console on next row: Segmentation fault (nothing else and the camera screen doesn´t appear) Do you have any idea, what could be wrong? I am quite desperate about it. I am not able to fix it on my own.
Support on raspberry pi 4b or not.
Thank alot,Your code is valid. I'm happy to support.
If you wanna try on 16GB A4000, please let me know. I can give you a cluster to test and benchmark. You can try single GPU as well as parallel processing with more GPUs to get super high performance that can even rival apache spark.
Hi I am looking for system that read LP for a Non-motorized Vehicle E bike and E Scooters I will be Happy to here if you heard about something like it
I loved your video, you explained everything with such a duplicity. Please make more video about data analysis. Thank you so much
You deserve all the good blessings mate thank you very much for your help anymore xero automations please keep them coming
Thank you so much.
May I ask how to Link large volumn of data among 2 excel files accurately , efficently and data (linkage) is link and locked at the excact cell (with $ sign)
You did a great job explaining this concept, cleaning data. I am looking forward to learning more from you.
Valeu!
Benchmark (Pandas vs Peaks vs Polars) ua-cam.com/video/1Kn665ADSck/v-deo.html