Complete Data Science Road Map🔥

with resources👇

1.Math and Statistics:
• Linear Algebra
• Calculus
• Probability
• Statistics

2.Languages:
• Python (
• NumPy,
• Pandas,
• Matplotlib,
• Seaborn )
• R

3. Data skills:
• Data Cleaning
• Exploratory Data Analysis
• Feature Engineering

4. Data Visualization:
• Matplotlib
• Seaborn
• Plotly
• Tableau

5.Machine Learning Basics:
• Supervised Learning
• Unsupervised Learning
• Regression
• Classification
• Clustering

6. ML Libraries:
• Scikit-Learn
• TensorFlow
• Keras
• PyTorch

7.Model Evaluation and Validation:
• Cross-Validation
• Hyperparameter Tuning
• Evaluation Metrics

8.Big Data Technologies:
• Apache Hadoop
• Apache Spark

9.Database:
• SQL Basics
• MySQL
• PostgreSQL

10.Deep Learning:
• Neural Networks
• CNN
• RNN
• Transfer Learning

11.Natural Language Processing (NLP):
• Tokenization
• Named Entity Recognition (NER)
• Sentiment Analysis

12.Time Series Analysis:
• Time Series Components
• Seasonal Decomposition
• Forecasting Methods

13.Model Deployment:
• Flask (for Python)
• Django (for Python)
• Docker

14.Version Control:
• Git
• GitHub

15. Cloud Platforms:
• AWS
• Azure
• GCP

16. Data Ethics and Privacy:
• Ethical Considerations
• Privacy Protection

17.Communication and Reporting:
• Data Storytelling
• Reporting Tools e.g.
- Jupyter Notebooks
- R Markdown

18.Continuous Learning:
• Stay Updated with Industry Trends
• Participate in Online Communities
• Join online Conferences

------------------- END --------------------

Some good resources to learn Data Science

Books:
• Python for Data Analysis
- by Wes McKinney
• Hands-On Machine Learning
- by Aurélien Géron
• The Art of Data Science
- by Roger D. Peng and Elizabeth M.
• Data Science from Scratch
-by Joel Grus

Blogs:
• Towards Data Science
• KDnuggets
• R-bloggers
• Flowingdata
• Analytics Vidhya

YouTube Channel
❯ Python ➟ Corey Schafer
❯ SQL ➟ Joey Blue
❯ Excel ➟ ExcelIsFun
❯ PowerBI ➟ Guy in a Cube
❯ Tableau ➟ Tableau Tim
❯ Mathematics ➟ 3Blue1Brown
❯ Statistics ➟ statquest
❯ Data Analyst ➟ AlexTheAnalyst
❯ ML, DL ➟ sentdex

Podcasts:
• Data Science at Home
• Talking Machines
• O'Reilly Data Science Podcast
• Linear Digressions
• DataFramed

Community and Forums:
Stack Overflow
Reddit - r/datascience:

Documentation and Guides:
1.Scikit-Learn Documentation:
Official documentation for the Scikit-Learn library.
2.Pandas Documentation: Official documentation for the Pandas library.

Book 📖 📕 📘

Basic Math for Game Development with Unity 3D

https://t.me/c/2109572262/737

Pdf in Resources group

PYTHON PROGRAMS pdf

What is the output of this code, and why?

Answer is 1. Because:

1️⃣.inner() function is defined inside outer(), but it has its own local variable x with the value of 2. Note that this inner x is different from the outer x.

2️⃣.inner() function is called inside outer(), but its return value (which is 2) is not stored or used in any way.

3️⃣.Finally, outer() returns the value of its own x, which is 1.

4️⃣.The print(outer()) statement calls outer() and prints the returned value, which is 1.

#Python vs. R

What will be the Output ?

Answer is C.)

Simply, because there's no code inside the try block that raises an exception, the except block is not executed, and the code continues to print "3" after executing the try block.

As a web developer today, most of your works are related to APIs.

But most of developers don't actually understand what it is. 👀

When we talk about API, we are usually referring to Web API. 🌐

Web API (Application Programmatic Interface) can provide:

1. Resources, e.g. bus arrival time, restaurant ratings...
2. Services or microservices, e.g. converting coordinates into place names, creating QR codes...

With Web APIs, developers can then easily incorporate these building blocks into other web applications.

👩‍💻There's some features of different Web API, for example:

1. Public vs. private
- Public APIs are available to everyone, but may subject to licenses
- Private APIs are only available to internal developers

2. Free vs. premium
- Premium APIs may charge on-demand
- That's why there's also this term “API Economy”!

There's actually API marketplace and directory site, like
- RapidAPI
- ProgrammableWeb

Here's some example of public API that you can explore:

1. Google (developers.google.com/apis-explorer)

2. Facebook (developers.facebook.com/docs/apis-and-…)

3. Data portals of many cities (dataportals.org/search)And you also have to understand what is 'API endpoints'.

API usually provides endpoints as a URI to provide services.

And it needs to be static, without affecting applications built upon ✨And that's why there's a standard for writing API called REST.

REST stands for 'REpresentational State Transfer'.

It's an architectural style of writing APIs.