7 level of writing Python Dictionary



Level 1: Basic Dictionary Creation

Level 2: Accessing and Modifying values

Level 3: Adding and Removing key Values Pairs

Level 4: Dictionary Methods

Level 5: Dictionary Comprehensions

Level 6: Nested Dictionary

Level 7: Advanced Dictionary Operations

I have curated the best interview resources to crack Python Interviews 👇👇
https://topmate.io/coding/898340

Hope you'll like it

Like this post if you need more resources like this 👍❤️

Artificial intelligence can change your career by 180 degrees! 📌

Here's how you can start with AI engineering with zero experience!

The simplest definition of artificial intelligence|

Artificial intelligence (AI) is a part of computer science that creates smart systems to solve problems usually needing human intelligence.

AI includes tasks like recognizing objects and patterns, understanding voices, making predictions, and more.

Step 1: Master the prerequisites

Basics of programming
Probability and statistics essentials
Data structures
Data analysis essentials

Step 2: Get into machine learning and deep learning

Basics of data science, an intersection field
Feature engineering and machine learning
Neural networks and deep learning
Scikit-learn for machine learning along with Numpy, Pandas and matplotlib
TensorFlow, Keras and PyTorch for deep learning

Step 3: Exploring Generative Adversarial Networks (GANs)

Learn GAN fundamentals: Understand the theory behind GANs, including how the generator and discriminator work together to produce realistic data.

Hands-on projects: Build and train simple GANs using PyTorch or TensorFlow to generate images, enhance resolution, or perform style transfer.

Step 4: Get into Transformers architecture

Grasp the basics: Study the Transformer architecture's key concepts, including attention mechanisms, positional encodings, and the encoder-decoder structure.
Implementations: Use libraries like Hugging Face’s Transformers to experiment with different Transformer models, such as GPT and BERT, on NLP tasks.

Step 5: Working with Pre-trained Large Language Models

Utilize existing models: Learn how to leverage pre-trained models from libraries like Hugging Face to perform tasks like text generation, translation, and sentiment analysis.

Fine-tuning techniques: Explore strategies for fine-tuning these models on domain-specific datasets to improve performance and relevance.

Step 6: Introduction to LangChain

Understand LangChain: Familiarize yourself with LangChain, a framework designed to build applications that combine language models with external knowledge and capabilities.

Build applications: Use LangChain to develop applications that interactively use language models to process and generate information based on user queries or tasks.

Step 7: Leveraging Vector Databases

Basics of vector databases: Understand what vector databases are and why they are crucial for managing high-dimensional data typically used in AI models.
Tools and technologies: Learn to use vector databases like Milvus, Pinecone, or Weaviate, which are optimized for fast similarity search and efficient handling of vector embeddings.
Practical application: Integrate vector databases into your projects for enhanced search functionalities

Step 8: Exploration of Retrieval-Augmented Generation (RAG)

Learn the RAG approach: Understand how RAG models combine the power of retrieval (extracting information from a large database) with generative models to enhance the quality and relevance of the outputs.

Practical applications: Study case studies or research papers that showcase the use of RAG in real-world applications.

Step 9: Deployment of AI Projects

Deployment tools: Learn to use tools like Docker for containerization, Kubernetes for orchestration, and cloud services (AWS, Azure, Google Cloud) for deploying models.

Monitoring and maintenance: Understand the importance of monitoring AI systems post-deployment and how to use tools like Prometheus, Grafana, and Elastic Stack for performance tracking and logging.

Step 10: Keep building

Implement Projects and Gain Practical Experience

Work on diverse projects: Apply your knowledge to solve problems across different domains using AI, such as natural language processing, computer vision, and speech recognition.

Contribute to open-source: Participate in AI projects and contribute to open-source communities to gain experience and collaborate with others.

Hope this helps you ☺️

𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍

Master Python, Machine Learning, SQL, and Data Visualization with hands-on tutorials & real-world datasets? 🎯

This 100% FREE resource from Kaggle will help you build job-ready skills—no fluff, no fees, just pure learning!

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/3XYAnDy

Perfect for Beginners ✅️

Best programming language suited for different fields:

1. Web development - Javanoscript, Python, PHP
2. AI & ML- Python, R
3. Competitive Programming - C++, Java
4. Mobile App development - Swift, Kotlin
5. Game Development - C#, C++
6. DSA- Java, Python
7. Data Analysis - Python, R
8. Data Science and ML - Python, R
9. Blockchain Dev- C++, Solidity
10. HFTs- C++, Java
11. Systems Programming - Rust, C
12. Embedded Systems - C, Assembly
13. Cybersecurity - Python, C
14. Financial Technology (Fintech) - Java, Scala
15. Internet of Things (IOT) - C, Python
16. Cloud Computing - Go, Java
17. DevOps & Automation - Python, Ruby
18. Scientific Computing - Fortran, Julia

𝗕𝗿𝗲𝗮𝗸 𝗜𝗻𝘁𝗼 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 – 𝗡𝗼 𝗘𝘅𝗰𝘂𝘀𝗲𝘀!😍

Want to learn Data Analytics, Python, Power BI, and Machine Learning without spending a single rupee?

Here’s your golden ticket! 🎟️

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/3DMG9S5

🔗 Bookmark & Share This With Someone Who Needs It!

𝟰 𝗙𝗥𝗘𝗘 𝗦𝗤𝗟 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍

- Introduction to SQL (Simplilearn) 

- Intro to SQL (Kaggle) 

- Introduction to Database & SQL Querying 

- SQL for Beginners – Microsoft SQL Server

 Start Learning Today – 4 Free SQL Courses

𝐋𝐢𝐧𝐤 👇:-

https://pdlink.in/42nUsWr

Enroll For FREE & Get Certified 🎓

𝗣𝗮𝘆 𝗔𝗳𝘁𝗲𝗿 𝗣𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 - 𝗟𝗲𝗮𝗿𝗻 𝗙𝗿𝗼𝗺 𝗧𝗵𝗲 𝗧𝗼𝗽 𝟭% 𝗼𝗳 𝘁𝗵𝗲 𝗧𝗲𝗰𝗵 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 😍

Start Learning Coding From Scratch - Get Placed In Top MNCs 

Curriculum designed and taught by Alumni from IITs & Leading Tech Companies.

𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀:-

10+ Hiring Drives Every Month 

🌟 Trusted by 7500+ Students
🤝 500+ Hiring Partners
💼 Avg. Package: ₹7.2 LPA | Highest: ₹41 LPA

Eligibility: BTech / BCA / BSc / MCA / MSc

𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐍𝐨𝐰 👇:-

 https://pdlink.in/4hO7rWY

Hurry! Limited seats are available.🏃‍♂️

⭕️ G-Mail keyboard shortcuts ⭕️
#pc_feature #OldPost

Here is the complete list of Gmail keyboard shortcuts:

Compose and Chat

<Shift> + <Esc> : Focus main window
<Esc> : Focus latest chat or compose
<Ctrl> + . : Advance to next chat or compose
<Ctrl> + , : Advance to previous chat or compose
<Ctrl> + <Enter> : Send
<Ctrl> + <Shift> + c : Add cc recipients
<Ctrl> + <Shift> + b : Add bcc recipients
<Ctrl> + <Shift> + f : Access custom from
<Ctrl> + k : Insert a link
<Ctrl> + ; : Go to previous misspelled word
<Ctrl> + ' : Go to next misspelled word
<Ctrl> + m : Open spelling suggestions

Formatting

<Ctrl> + <Shift> + 5 : Previous font
<Ctrl> + <Shift> + 6 : Next font
<Ctrl> + <Shift> + - : Decrease text size
<Ctrl> + <Shift> + + : Increase text size
<Ctrl> + b : Bold
<Ctrl> + i : Italics
<Ctrl> + u : Underline
<Ctrl> + <Shift> + 7 : Numbered list
<Ctrl> + <Shift> + 8 : Bulleted list
<Ctrl> + <Shift> + 9 : Quote
<Ctrl> + [ : Indent less
<Ctrl> + ] : Indent more
<Ctrl> + <Shift> + l : Align left
<Ctrl> + <Shift> + e : Align center
<Ctrl> + <Shift> + r : Align right
<Ctrl> + <Shift> + , : Set right-to-left
<Ctrl> + <Shift> + . : Set left-to-right
<Ctrl> + \ : Remove formatting


Jumping

g then i : Go to Inbox
g then s : Go to Starred conversations
g then t : Go to Sent messages
g then d : Go to Drafts
g then a : Go to All mail
g then c : Go to Contacts
g then k : Go to Tasks
g then l : Go to Label

Threadlist selection

* then a : Select all conversations
* then n : Deselect all conversations
* then r : Select read conversations
* then u : Select unread conversations
* then s : Select starred conversations
* then t : Select unstarred conversations

Navigation

u : Back to threadlist
k / j : Newer/older conversation
o or <Enter> : Open conversation; collapse/expand conversation
p / n : Read previous/next message
` : Go to next inbox section
~ : Go to previous inbox section

Application

c : Compose
d : Compose in a tab (new compose only)
/ : Search mail
q : Search chat contacts
. : Open "more actions" menu
v : Open "move to" menu
l : Open "label as" menu
? : Open keyboard shortcut help

Actions

, : Move focus to toolbar
x : Select conversation
s : Rotate superstar
y : Remove label
e : Archive
m : Mute conversation
! : Report as spam
# : Delete
r : Reply
<Shift> + r : Reply in a new window
a : Reply all
<Shift> + a : Reply all in a new window
f : Forward
<Shift> + f : Forward in a new window
<Shift> + n : Update conversation
] / [ :  Remove conversation from current view and go previous/next
} / { : Archive conversation and go previous/next
z : Undo last action
<Shift> + i : Mark as read
<Shift> + u : Mark as unread
_ : Mark unread from the selected message
+ or = : Mark as important
- : Mark as not important
<Shift> + t : Add conversation to Tasks

𝗖𝗶𝘀𝗰𝗼 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍

Upgrade Your Tech Skills in 2025—For FREE!

🔹 Introduction to Cybersecurity
🔹 Networking Essentials
🔹 Introduction to Modern AI
🔹 Discovering Entrepreneurship
🔹 Python for Beginners

𝐋𝐢𝐧𝐤 👇:-

https://pdlink.in/4chn8Us

Enroll For FREE & Get Certified 🎓

Free YouTube Resources 👆