Do you want to attend Machine Learning events online or in person? If yes, here is the list of upcoming conferences, webinars, workshops, summits, and events to happen in 2022 and 2023. @DataNomadKE
https://t.co/hnhPJfy723 #MachineLearning#datascience#AI#DataAnalytics#AI
Microsoft Fabric is here!!
But what is it?
This is a new end-to-end data and analytics platform,
human-centered analytics product that brings together all of an organization's data and analytics in one place.
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#MicrosoftFabric
Congratulations to the newest Microsoft Valuable Professional #MVPBuzz 🥳🔥. Super grateful for the amount of work and time you take to give back to the community. @myles_shadrack
It's amazing how you've being a great lead for the #PowerPlatform user group Kenya.
DevOps culture has taken over the software industry and permanently changed the way many organizations do their work. Join us this Saturday from 10 am to 12 pm for an introductory workshop on DevOps Engineering. You will learn the culture of DevOps, practices and tools that...
3. Text analysis
This is done through text features analysis like wordcloud and N-gram analysis.
To conclude, EDA is important before building models using Algorithms. First, comprehend the data deeply.
#EDA#DataScience#MachineLearning#dataanalysis
2. EDA importance?
Before applying any ML algorithms in data, we need to understand the data which we are going to follow. Without data understanding there will be a possibility of ML model failure.
Data Understanding is Exploratory Data Analysis (EDA).
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In DS and ML forums, I have heard panelists share that one should not do EDA before ML because it may cause bias to the results. My take is failing to inquire and comprehend data is a the real bias.
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a).What is EDA?
b). Is EDA important before ML?
1. Exploratory Data Analysis (EDA) is the process of using summary statistics and graphical representations to perform initial inquiries on data to discover patterns, detect anomalies, test hypotheses, and verify assumptions.
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30Days of Data Science is coming back. October 2022, you will build and deploy ML models such as Fraud Detection Model, Product Pricing Model, etc on Azure Cloud.
We will guide you through these projects.
Who is Excited?
@BethanyJep@lee_stott@japhletnwamu
Share your work more on Github. A good way of doing this is by joining a Kaggle competition. A learning and practice competition would do. Link your GitHub and Kaggle. Every time you save changes on your Notebook, it will update the Git repository. #datascience#Productivity
In 2012, Havard Business Review dropped one of the most capturing Data Science articles which called the role of a data scientist as “the sexiest job of the 21st century”. A decade later, HBR did a review and asked if 'Data Science is still the sexiest job?" My takeaways.
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Power Apps Functions Day 2
Error Handling is vital in Power apps. @ShanesCows does a very comprehensive error handling using On Error property.
The most interesting part, one can store all errors on your data source like SP. https://t.co/GI1G7NFOkC
#powerapps#PowerPlatform
Today I learnt how to get Emails on Power Apps. This is a very cool functionality. I have always flagged emails from power apps but never displayed Email content on Power apps. So cool!😎
#PowerApps#PowerPlatform