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Coding Interview Resources

Coding Interview Resources

前往频道在 Telegram

This channel contains the free resources and solution of coding problems which are usually asked in the interviews. Managed by: @love_data

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📈 Telegram 频道 Coding Interview Resources 的分析概览

频道 Coding Interview Resources (@crackingthecodinginterview) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 52 120 名订阅者,在 技术与应用 类别中位列第 2 563,并在 印度 地区排名第 7 263

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 52 120 名订阅者。

根据 05 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 194,过去 24 小时变化为 11,整体触达仍然可观。

  • 认证状态: 未认证
  • 互动率 (ER): 平均受众互动率为 1.93%。内容发布后 24 小时内通常能获得 0.84% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 1 005 次浏览,首日通常累积 437 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 2
  • 主题关注点: 内容集中在 array, stack, algorithm, programming, sort 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台:
This channel contains the free resources and solution of coding problems which are usually asked in the interviews. Managed by: @love_data

凭借高频更新(最新数据采集于 07 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。

52 120
订阅者
+1124 小时
+407
+19430
帖子存档
The Only roadmap you need to become an ML Engineer 🥳 Phase 1: Foundations (1-2 Months) 🔹 Math & Stats Basics – Linear Algebra, Probability, Statistics 🔹 Python Programming – NumPy, Pandas, Matplotlib, Scikit-Learn 🔹 Data Handling – Cleaning, Feature Engineering, Exploratory Data Analysis Phase 2: Core Machine Learning (2-3 Months) 🔹 Supervised & Unsupervised Learning – Regression, Classification, Clustering 🔹 Model Evaluation – Cross-validation, Metrics (Accuracy, Precision, Recall, AUC-ROC) 🔹 Hyperparameter Tuning – Grid Search, Random Search, Bayesian Optimization 🔹 Basic ML Projects – Predict house prices, customer segmentation Phase 3: Deep Learning & Advanced ML (2-3 Months) 🔹 Neural Networks – TensorFlow & PyTorch Basics 🔹 CNNs & Image Processing – Object Detection, Image Classification 🔹 NLP & Transformers – Sentiment Analysis, BERT, LLMs (GPT, Gemini) 🔹 Reinforcement Learning Basics – Q-learning, Policy Gradient Phase 4: ML System Design & MLOps (2-3 Months) 🔹 ML in Production – Model Deployment (Flask, FastAPI, Docker) 🔹 MLOps – CI/CD, Model Monitoring, Model Versioning (MLflow, Kubeflow) 🔹 Cloud & Big Data – AWS/GCP/Azure, Spark, Kafka 🔹 End-to-End ML Projects – Fraud detection, Recommendation systems Phase 5: Specialization & Job Readiness (Ongoing) 🔹 Specialize – Computer Vision, NLP, Generative AI, Edge AI 🔹 Interview Prep – Leetcode for ML, System Design, ML Case Studies 🔹 Portfolio Building – GitHub, Kaggle Competitions, Writing Blogs 🔹 Networking – Contribute to open-source, Attend ML meetups, LinkedIn presence Follow this advanced roadmap to build a successful career in ML! The data field is vast, offering endless opportunities so start preparing now.

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Best way to prepare for a SQL interviews 👇👇 1. Review Basic Concepts: Ensure you understand fundamental SQL concepts like SELECT statements, JOINs, GROUP BY, and WHERE clauses. 2. Practice SQL Queries: Work on writing and executing SQL queries. Practice retrieving, updating, and deleting data. 3. Understand Database Design: Learn about normalization, indexes, and relationships to comprehend how databases are structured. 4. Know Your Database: If possible, find out which database system the company uses (e.g., MySQL, PostgreSQL, SQL Server) and familiarize yourself with its specific syntax. 5. Data Types and Constraints: Understand various data types and constraints such as PRIMARY KEY, FOREIGN KEY, and UNIQUE constraints. 6. Stored Procedures and Functions: Learn about stored procedures and functions, as interviewers may inquire about these. 7. Data Manipulation Language (DML): Be familiar with INSERT, UPDATE, and DELETE statements. 8. Data Definition Language (DDL): Understand statements like CREATE, ALTER, and DROP for database and table management. 9. Normalization and Optimization: Brush up on database normalization and optimization techniques to demonstrate your understanding of efficient database design. 10. Troubleshooting Skills: Be prepared to troubleshoot queries, identify errors, and optimize poorly performing queries. 11. Scenario-Based Questions: Practice answering scenario-based questions. Understand how to approach problems and design solutions. 12. Latest Trends: Stay updated on the latest trends in database technologies and SQL best practices. 13. Review Resume Projects: If you have projects involving SQL on your resume, be ready to discuss them in detail. 14. Mock Interviews: Conduct mock interviews with a friend or use online platforms to simulate real interview scenarios. 15. Ask Questions: Prepare questions to ask the interviewer about the company's use of databases and SQL. Best Resources to learn SQL 👇 SQL Topics for Data Analysts SQL Udacity Course Download SQL Cheatsheet SQL Interview Questions Learn & Practice SQL Also try to apply what you learn through hands-on projects or challenges. Please give us credits while sharing: -> https://t.me/free4unow_backup ENJOY LEARNING 👍👍

𝗪𝗮𝗻𝘁 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗝𝗮𝘃𝗮 𝘁𝗵𝗲 𝗘𝗮𝘀𝘆 𝗪𝗮𝘆?😍 Learning Java doesn’t have to be overwhelming✨️ Whether you’re pr
𝗪𝗮𝗻𝘁 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗝𝗮𝘃𝗮 𝘁𝗵𝗲 𝗘𝗮𝘀𝘆 𝗪𝗮𝘆?😍 Learning Java doesn’t have to be overwhelming✨️ Whether you’re preparing for placements, brushing up for coding interviews, or just starting your programming journey, these 4 free playlists are your shortcut to success! 🚀 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/401OSrs 💫Pro Tip:- Start with any one playlist and stay consistent. Java gets easier when you code along, build mini-projects, and revise concepts regularly✅️

In 1994, people told me programming was for nerds and that I should become a doctor or a lawyer instead. 10 years later, they told me that someone from India would take my job for $5/hour. Then, no code was going to doom my career. In 2021, Codex, then Copilot, then ChatGPT, then Devin, then OpenAI o1... People keep yelling that "Programming is Dead," and yet the demand for good Software Engineers has never been higher. Stop listening to midwit people. Learn to build good software, and you'll be okay. (Credits: unknown)

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9 tips to prepare for coding interviews: Master DSA fundamentals (arrays, strings, trees, graphs) Practice daily on LeetCode, Codeforces, or HackerRank Solve problems under time constraints Review commonly asked interview patterns Mock interviews help reduce anxiety Understand the “why” behind each solution Prepare clean, structured explanations Brush up on system design and OOP basics Stay consistent — prep a little every day Coding Interview Resources:👇 https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X ENJOY LEARNING 👍👍

𝗪𝗮𝗻𝘁 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗜𝗻-𝗗𝗲𝗺𝗮𝗻𝗱 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 — 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 — 𝗗𝗶𝗿𝗲𝗰𝘁𝗹𝘆 𝗳𝗿𝗼𝗺 𝗚𝗼𝗼𝗴𝗹𝗲?�
𝗪𝗮𝗻𝘁 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗜𝗻-𝗗𝗲𝗺𝗮𝗻𝗱 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 — 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 — 𝗗𝗶𝗿𝗲𝗰𝘁𝗹𝘆 𝗳𝗿𝗼𝗺 𝗚𝗼𝗼𝗴𝗹𝗲?😍 Whether you’re a student, job seeker, or just hungry to upskill — these 5 beginner-friendly courses are your golden ticket🎟️ No fluff. No fees. Just career-boosting knowledge and certificates that make your resume pop✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/42vL6br Enjoy Learning ✅️

Here are 20 essential VS Code shortcuts for beginners: 1. Ctrl + P: Open any file quickly 📂 2. Ctrl + /: Toggle line comment 📝 3. Alt + Up/Down: Move a line up or down ↕️ 4. Ctrl + Shift + K: Delete the current line ❌ 5. Ctrl + B: Show/hide the sidebar 📚 6. Ctrl + Space: Trigger IntelliSense for code suggestions 💡 7. Ctrl + Shift + F: Search across files 🔍 8. Ctrl + D: Select the next occurrence of the selected text 📑 9. Ctrl + Shift + L: Select all occurrences of the current selection 🔗 10. Ctrl + Shift + P: Open the Command Palette 📜 11. Ctrl + F2: Rename all occurrences of a variable ✏️ 12. Ctrl + J: Show/hide the integrated terminal 💻 13. Ctrl + `: Open a new terminal 🔧 14. Ctrl + Shift + N: Open a new window 🖼️ 15. Ctrl + W: Close the current editor tab 🗂️ 16. Ctrl + Shift + E: Focus on the file explorer 🗃️ 17. Ctrl + Shift + G: Open the Git view 🔄 18. Ctrl + Shift + M: Open the Problems panel 🚨 19. Alt + Shift + Up/Down: Copy the line up or down 📋 20. Ctrl + Alt + Arrow keys: Split the editor window ✂️ Master these and level up your coding speed! 🚀

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Top 50 OOPS Interview Preparation Course 💻✅
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Top 50 OOPS Interview Preparation Course 💻✅

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𝗪𝗮𝗻𝘁 𝘁𝗼 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗶𝗻 𝟮𝟬𝟮𝟱? 𝗛𝗲𝗿𝗲'𝘀 𝗬𝗼𝘂𝗿 𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 �
𝗪𝗮𝗻𝘁 𝘁𝗼 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗶𝗻 𝟮𝟬𝟮𝟱? 𝗛𝗲𝗿𝗲'𝘀 𝗬𝗼𝘂𝗿 𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗮𝘁𝗵!😍 Skip the pricey courses — and start learning with these 5 YouTube playlists that cover everything from Excel and SQL to Power BI and real-world portfolio projects👨‍💻 Whether you’re a student, career switcher, or just brushing up for interviews, this list will give you all the tools you need — step by step.📊📌 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4eAK4Pv Save this post & start watching today.✅️

Here are some essential SQL tips for beginners 👇👇 ◆ Primary Key = Unique Key + Not Null constraint ◆ To perform case insensitive search use UPPER() function ex. UPPER(customer_name) LIKE ‘A%A’ ◆ LIKE operator is for string data type ◆ COUNT(*), COUNT(1), COUNT(0) all are same ◆ All aggregate functions ignore the NULL values ◆ Aggregate functions MIN, MAX, SUM, AVG, COUNT are for int data type whereas STRING_AGG is for string data type ◆ For row level filtration use WHERE and aggregate level filtration use HAVING ◆ UNION ALL will include duplicates where as UNION excludes duplicates  ◆ If the results will not have any duplicates, use UNION ALL instead of UNION ◆ We have to alias the subquery if we are using the columns in the outer select query ◆ Subqueries can be used as output with NOT IN condition. ◆ CTEs look better than subqueries. Performance wise both are same. ◆ When joining two tables , if one table has only one value then we can use 1=1 as a condition to join the tables. This will be considered as CROSS JOIN. ◆ Window functions work at ROW level. ◆ The difference between RANK() and DENSE_RANK() is that RANK() skips the rank if the values are the same. ◆ EXISTS works on true/false conditions. If the query returns at least one value, the condition is TRUE. All the records corresponding to the conditions are returned. Like for more 😄😄

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Complete DSA Roadmap |-- Basic_Data_Structures | |-- Arrays | |-- Strings | |-- Linked_Lists | |-- Stacks | └─ Queues | |-- Advanced_Data_Structures | |-- Trees | | |-- Binary_Trees | | |-- Binary_Search_Trees | | |-- AVL_Trees | | └─ B-Trees | | | |-- Graphs | | |-- Graph_Representation | | | |- Adjacency_Matrix | | | └ Adjacency_List | | | | | |-- Depth-First_Search | | |-- Breadth-First_Search | | |-- Shortest_Path_Algorithms | | | |- Dijkstra's_Algorithm | | | └ Bellman-Ford_Algorithm | | | | | └─ Minimum_Spanning_Tree | | |- Prim's_Algorithm | | └ Kruskal's_Algorithm | | | |-- Heaps | | |-- Min_Heap | | |-- Max_Heap | | └─ Heap_Sort | | | |-- Hash_Tables | |-- Disjoint_Set_Union | |-- Trie | |-- Segment_Tree | └─ Fenwick_Tree | |-- Algorithmic_Paradigms | |-- Brute_Force | |-- Divide_and_Conquer | |-- Greedy_Algorithms | |-- Dynamic_Programming | |-- Backtracking | |-- Sliding_Window_Technique | |-- Two_Pointer_Technique | └─ Divide_and_Conquer_Optimization | |-- Merge_Sort_Tree | └─ Persistent_Segment_Tree | |-- Searching_Algorithms | |-- Linear_Search | |-- Binary_Search | |-- Depth-First_Search | └─ Breadth-First_Search | |-- Sorting_Algorithms | |-- Bubble_Sort | |-- Selection_Sort | |-- Insertion_Sort | |-- Merge_Sort | |-- Quick_Sort | └─ Heap_Sort | |-- Graph_Algorithms | |-- Depth-First_Search | |-- Breadth-First_Search | |-- Topological_Sort | |-- Strongly_Connected_Components | └─ Articulation_Points_and_Bridges | |-- Dynamic_Programming | |-- Introduction_to_DP | |-- Fibonacci_Series_using_DP | |-- Longest_Common_Subsequence | |-- Longest_Increasing_Subsequence | |-- Knapsack_Problem | |-- Matrix_Chain_Multiplication | └─ Dynamic_Programming_on_Trees | |-- Mathematical_and_Bit_Manipulation_Algorithms | |-- Prime_Numbers_and_Sieve_of_Eratosthenes | |-- Greatest_Common_Divisor | |-- Least_Common_Multiple | |-- Modular_Arithmetic | └─ Bit_Manipulation_Tricks | |-- Advanced_Topics | |-- Trie-based_Algorithms | | |-- Auto-completion | | └─ Spell_Checker | | | |-- Suffix_Trees_and_Arrays | |-- Computational_Geometry | |-- Number_Theory | | |-- Euler's_Totient_Function | | └─ Mobius_Function | | | └─ String_Algorithms | |-- KMP_Algorithm | └─ Rabin-Karp_Algorithm | |-- OnlinePlatforms | |-- LeetCode | |-- HackerRank

𝟭𝟱-𝗗𝗮𝘆 𝗣𝘆𝘁𝗵𝗼𝗻 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝘄𝗶𝘁𝗵 𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀!😍 Want to master Python but don’t know where to
𝟭𝟱-𝗗𝗮𝘆 𝗣𝘆𝘁𝗵𝗼𝗻 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝘄𝗶𝘁𝗵 𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀!😍 Want to master Python but don’t know where to start? 🤔 Here’s a structured 15-day roadmap with handpicked FREE resources to help you learn Python from scratch!👨‍💻📌 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3Xrs6rr ✨️Bonus: Includes FREE tutorials, YouTube playlists, and coding exercises!✅️

When you’re in an interview, it’s super important to know how to talk about your projects in a way that impresses the interviewer. Here are some key points to help you do just that: ➤ 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗢𝘃𝗲𝗿𝘃𝗶𝗲𝘄: - Start with a quick summary of the project you worked on. What was it all about? What were the main goals? Keep it short and sweet something you can explain in about 30 seconds. ➤ 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁: - What problem were you trying to solve with this project? Explain why this problem was important and needed addressing. ➤ 𝗣𝗿𝗼𝗽𝗼𝘀𝗲𝗱 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: - Describe the solution you came up with. How does it work, and why is it a good fix for the problem? ➤ 𝗬𝗼𝘂𝗿 𝗥𝗼𝗹𝗲: - Talk about what you specifically did. What were your main tasks? Did you face any challenges, and how did you overcome them? Make sure it’s clear whether you were leading the project, a key player, or supporting the team. ➤ 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗮𝗻𝗱 𝗧𝗼𝗼𝗹𝘀: - Mention the tech and tools you used. This shows your technical know-how and your ability to choose the right tools for the job. ➤ 𝗜𝗺𝗽𝗮𝗰𝘁 𝗮𝗻𝗱 𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁𝘀: - Share the results of your project. Did it make things better? How? Mention any improvements, efficiencies, or positive feedback you got. ➤ 𝗧𝗲𝗮𝗺 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻: - Talk about how you collaborated. What was your role in the team? How did you communicate and contribute to the team’s success? ➤ 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: - Reflect on what you learned from the project. What new skills did you gain, and what would you do differently next time? ➤ 𝗧𝗶𝗽𝘀 𝗳𝗼𝗿 𝗬𝗼𝘂𝗿 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻: - Be ready with a 30 second elevator pitch about your projects, and also have a five-minute detailed overview ready. - If there’s a pause after you describe the project, don’t hesitate to ask if they’d like more details or if there’s a specific part they’re interested in. By preparing your project details thoroughly and understanding what the interviewer is looking for, you can talk about your experience in a way that really showcases your skills and increases your chances of getting the job. Coding Projects: https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502

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