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Sumanth 🚀 Profile picture
@Sumanth_077
Aug 12 • 7 tweets • 2 min read Twitter logo Read on Twitter
Become a Microsoft Certified Data Analyst🧑‍🎓

Thread 🧵👇 Image
1. Get started with Microsoft data analytics

learn.microsoft.com/en-us/training…
2. Prepare data for analysis with Power BI

learn.microsoft.com/en-us/training…
3. Model data with Power BI

learn.microsoft.com/en-us/training…
4. Build Power BI visuals and reports

learn.microsoft.com/en-us/training…
5. Certification

All the above Courses are free but certification is paid.

You need to take a certification exam.

Check this out:

learn.microsoft.com/en-us/certific…
That's a wrap!

If you are interested in any of these below topics:

- Python 🐍
- Data Science 📈
- Machine Learning 🤖
- Data Analysis 📊
- LLMs 🧠
- MLOps 🛠

Find me → @Sumanth_077 ✅

I'm sharing daily content over here.

• • •

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More from @Sumanth_077

Sumanth 🚀 Profile picture
Aug 5
Harvard University is offering online courses on:

- Python
- Data Science
- Machine Learning
- Data Preprocessing
- Data Visualization &
- Statistics

No application required!

Here are 5 FREE courses you don't want to miss:

Thread🧵👇 Image
1. Python:

CS50’s Introduction to Programming with Python offered by Harvard.

You will learn concepts like functions, arguments, variables, data types, conditional statements, loops, objects, methods, and more.

edx.org/course/cs50s-i…
2. Statistics:

Learn the fundamentals of statistics required for Data Science

edx.org/learn/data-ana…
Read 9 tweets
Sumanth 🚀 Profile picture
Aug 4
If you are using jupyter notebooks for Python and Data Science, try these 7 magic commands that will save you a ton of time:🧵

1. Jupyter AI: Select any model and chat with it right from the Jupyter Notebook. Image
Use the "%%ai" magic command to specify a model chat with the model using a natural language prompt:

Check this out: github.com/jupyterlab/jup…
2. %%latex:

This helps you to display LaTeX code in Jupyter Notebook

Here is how you can do that: Image
Read 8 tweets
Sumanth 🚀 Profile picture
Jul 29
MIT university is offering FREE education in Data Science.

Courses cover:

- Python
- Data Science
- Machine Learning
- Statistics
- Linear Algebra &
- Deep Learning

Learn from the best at a free of cost!

Thread🧵👇 Image
1. Introduction to Computer Science and Programming in Python

A great course to learn the fundamentals of computer science in Python

https://t.co/H1T8pySXtrocw.mit.edu/courses/6-0001…
Image
2. Linear Algebra

Get an overview of the important and basic concepts of Linear Algebra required for Machine Learning

ocw.mit.edu/courses/res-18…
Read 7 tweets
Sumanth 🚀 Profile picture
Jul 26
If you are looking for Public Datasets to work on Data Science & Machine Learning.

Here are 8 Free Data Sources where you can find one for your next Project:

Thread🧵👇 Image
1. Kaggle

No Introduction is required to kaggle, you can find 1000's datasets which you can download and use for free

Check it out here:👇

kaggle.com/datasets
2. Open Data Registry on AWS

Find and share datasets through AWS resources.

Check this out:👇

registry.opendata.aws
Read 10 tweets
Sumanth 🚀 Profile picture
Jul 25
Neural Network implemented from scratch in Python🔥

Here is the step by step explanation with code.

Thread🧵👇 Image
Below is the simple Neural Network consists of 2 layers:

- Hidden Layer
- Output Layer

First Initialize the size of layers along with the weights & biases.

And also define the sigmoid activation function & it's derivative which is really key to introduce non-linearity. Image
Forward Pass:

Here the input data is passed through the neural network to obtain the predicted output.

In forward pass, First calculate the output of the hidden layer.

hidden_output = X•W1 + b1

Then apply the sigmoid activation to the output.

output = sigmoid( (X•W1) + b1) Image
Read 9 tweets
Sumanth 🚀 Profile picture
Jul 24
An open-source, low-code Python Library to automate the machine learning workflows:🔥

Introducing PyCaret an end-to-end Machine Learning tool that does:

- Data Preprocessing
- Feature Engineering
- Model training
- Hyperparameter tuning &
- Model Evaluation

Thread🧵👇 Image
To simplify PyCaret is a low-code library that helps in writing the ML workflow with just a few lines.

PyCaret's module supports both supervised learning (classification & regression) and unsupervised learning (clustering)

All you need to do is:

"pip install pycaret"
Here is doing Regression Task using Pycaret!

- Load the dataset
- Import the regression module and initialise the setup.
- Train & Evaluate the model
- Save the Model

Check this out:👇 Image
Read 6 tweets

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