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Priyanka Vergadia Profile picture
@pvergadia
Dec 2, 2021 • 12 tweets • 4 min read • Read on X
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Here's a brief introduction to @googlecloud 🧵
☁️ Infrastructure
☁️ Networking
☁️ Storage & Database
☁️ Data Analytics
☁️ ML/AI
☁️ Operations
☁️ Security
☁️ DevOps

🧵🪡
Infrastructure options:
🔹Compute Engine (GCE)
🔹Cloud Run
🔹Kubernetes Engine (GKE)
🔹Cloud Functions
Networking starts with VPC - Virtual Private Cloud
Big component of networking is balancing load across servers and services
🚥 Load balancing
Networking: Cloud CDN for delivery content to the user fast!
Networking: Cloud DNS: low-latency DNS service
Storage & Database choices in @googlecloud
Building a scalable Data Analytics pipeline in the cloud 👇
☁️ BigQuery - Data warehouse
☁️ Cloud Storage - Data lake
☁️ Dataflow - Data processing
☁️ Dataproc - Managed Hadoop
Machine learning & AI on @googlecloud
Monitoring, logging and operations in the cloud 👇
Security controls in the @googlecloud
🔐 Infrastructure security
🔐 Network security
🔐 Application security
🔐 Data security
🔐 Identity & access management
🔐 Security monitoring
🔐 Governance & compliance
This is a summary of the presentation I did a recently at @DevFest2021. You can checkout the talk here

Thanks @DThompsonDev for inviting me to present!

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More from @pvergadia

Priyanka Vergadia Profile picture
Jan 12, 2023
I have been in cloud tech for 10+ years. Here are some basic concepts that everyone in or aspiring to be in cloud should know!

Read on 👇
Cloud can be used in lots of different ways: IaaS, CaaS, PaaS, FaaS, SaaS
Here are the benefits of Cloud Computing?
Read 14 tweets
Priyanka Vergadia Profile picture
Dec 20, 2022
Here are a few click-to-deploy architectures available in our Architecture Diagramming Tool!
✅ Simple VM app
✅ 3 tier app
✅ Batch ETL pipeline
✅ Cost Management
✅ Static web hosting with domain
✅ Storage event function app Image
✅ Simple VM app
googlecloudcheatsheet.withgoogle.com/architecture?d… Image
✅ Batch ETL pipeline
googlecloudcheatsheet.withgoogle.com/architecture?d… Image
Read 8 tweets
Priyanka Vergadia Profile picture
Feb 28, 2021
Experimented with Teachable Machine today and created a #nocode classification model in less than 5 mins!

It's a web-based tool making #machinelearning models fast, easy, and accessible to everyone.

See how I did it 🧵👇

teachablemachine.withgoogle.com

#nocode #31DaysofML
How do I use it?

📌Gather data (upload it)
📌Train model (in the web interface)
📌Export the model (use it in your app) Image
What can I use to teach it?

📌Images
📌Sounds
📌Poses

We can use files or capture examples live through webcam/microphone. Image
Read 5 tweets
Priyanka Vergadia Profile picture
Feb 15, 2021
Day 14 #31DaysofML

🤔 How to pick the right #GoogleCloud #MachineLearning tool for your application?

Answer these questions
❓ What's your teams ML expertise?
❓ How much control/abstraction do you need?
❓ Would you like to handle the infrastructure components?

🧵 👇
@SRobTweets created this pyramid to explain the idea.
As you move up the pyramid, less ML expertise is required, and you also don’t need to worry as much about the infrastructure behind your model.

To lear more watch this video 👉

#31DaysofML 2/10
@SRobTweets If you’re using Open source ML frameworks (#TensorFlow) to build the models, you get the flexibility of moving your workloads across different development & deployment environments. But, you need to manage all the infrastructure yourself for training & serving

#31DaysofML 3/10
Read 10 tweets
Priyanka Vergadia Profile picture
Feb 14, 2021
Day 13 #31DaysofML

⚖️ How to deal with imbalanced datasets?⚖️
Most real-world datasets are not perfectly balanced. If 90% of your dataset belongs to one class, & only 10% to the other, how can you prevent your model from predicting the majority class 90% of the time?

🧵 👇
🐱🐱🐱🐱🐱🐱🐱🐱🐱🐶 (90:10)
💳 💳 💳 💳 💳 💳 💳 💳 💳 ⚠️ (90:10)
There can be many reasons for imbalanced data. First step is to see if it's possible to collect more data. If you're working with all the data that's available, these 👇 techniques can help

#31DaysofML 2/7
Here are 3 techniques for addressing data imbalance. You can use just one of these or all of them together:
⚖️ Downsampling
⚖️ Upsampling
⚖️ Weighted classes

#31DaysofML 3/7
Read 7 tweets
Priyanka Vergadia Profile picture
Feb 11, 2021
Since it is Day 10 of #31DaysofML it's perfect to discuss 1️⃣0️⃣ things that can go wrong with #MachineLearning Projects and what you can do about it!

I watched this amazing presentation by @kweinmeister that sums it all up

A 🧵 Image
@kweinmeister 1️⃣ You aren't solving the right problem
❓What's the goal of your ML model?
❓How do you assess if your model is "good" or "bad"?
❓What's your baseline?
👉 Focus on a long-term mission with maximum impact
👉 Ensure that your problem is a good fit for ML

#31DaysofML
@kweinmeister 2️⃣ Jumping into development without a prototype
👉 ML project is an iterative process
👉 Start with simple model & continue to refine it until you've reached your goal
👉 Quick prototype can tell a lot about hidden requirements, implementation challenges, scope, etc

#31DaysofML
Read 11 tweets

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