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Everything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_data

Сітка:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert Індія6 527 Технології та додатки2 375...

📈 Аналітичний огляд Telegram-каналу Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books

Канал Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books (@programming_guide) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 56 107 підписників, посідаючи 2 375 місце в категорії Технології та додатки та 6 527 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 56 107 підписників.

За останніми даними від 09 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 105, а за останні 24 години на 12, загальне охоплення залишається високим.

Статус верифікації: Не верифікований
Рівень залученості (ER): Середній показник залученості аудиторії становить 2.63%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.84% реакцій від загальної кількості підписників.
Охоплення публікацій: В середньому кожен допис отримує 1 473 переглядів. Протягом першої доби публікація в середньому набирає 470 переглядів.
Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 3.
Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як algorithm, structure, stack, javascript, programming.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“Everything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_data”

Завдяки високій частоті оновлень (останні дані отримано 10 червня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Технології та додатки.

56 107

Підписники

+1224 години

+527 днів

+10530 день

1 473

Перегляди допису

~ 47024 години

~ 68548 годин

2.63%

Коефіцієнт залучення

~ 1

Дописів на день

Ads index

beta

Архів дописів

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𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 - 𝗘𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘😍 Industry-approved Certifications to enhance employability 𝗔𝗜 & 𝗠𝗟 :- https://pdlink.in/4nwV054 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 :-https://pdlink.in/4l3nFx0 𝗖𝗹𝗼𝘂𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 :- https://pdlink.in/4lteAgN 𝗖𝘆𝗯𝗲𝗿 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 :- https://pdlink.in/3ZLHHmW 𝗢𝘁𝗵𝗲𝗿 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 :-https://pdlink.in/3G5G9O4 𝗠𝗼𝗰𝗸 𝗔𝘀𝘀𝗲𝘀𝘀𝗺𝗲𝗻𝘁:- https://pdlink.in/4kan6A9 Get the Govt. of India Incentives on course completion🎓

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𝟰 𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 & 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗵𝗮𝘁 𝗪𝗶𝗹𝗹 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗨𝗽𝗴𝗿𝗮𝗱𝗲 𝗬𝗼𝘂𝗿 𝗥𝗲𝘀𝘂𝗺𝗲😍 I failed my first data interview — and here’s why:⬇️ ❌ No structured learning ❌ No real projects ❌ Just random YouTube tutorials and half-read blogs If this sounds like you, don’t repeat my mistake✨️ Recruiters want proof of skills, not just buzzwords📊 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4ka1ZOl All The Best 🎊

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Machine Learning – Essential Concepts 🚀 1️⃣ Types of Machine Learning Supervised Learning – Uses labeled data to train models. Examples: Linear Regression, Decision Trees, Random Forest, SVM Unsupervised Learning – Identifies patterns in unlabeled data. Examples: Clustering (K-Means, DBSCAN), PCA Reinforcement Learning – Models learn through rewards and penalties. Examples: Q-Learning, Deep Q Networks 2️⃣ Key Algorithms Regression – Predicts continuous values (Linear Regression, Ridge, Lasso). Classification – Categorizes data into classes (Logistic Regression, Decision Tree, SVM, Naïve Bayes). Clustering – Groups similar data points (K-Means, Hierarchical Clustering, DBSCAN). Dimensionality Reduction – Reduces the number of features (PCA, t-SNE, LDA). 3️⃣ Model Training & Evaluation Train-Test Split – Dividing data into training and testing sets. Cross-Validation – Splitting data multiple times for better accuracy. Metrics – Evaluating models with RMSE, Accuracy, Precision, Recall, F1-Score, ROC-AUC. 4️⃣ Feature Engineering Handling missing data (mean imputation, dropna()). Encoding categorical variables (One-Hot Encoding, Label Encoding). Feature Scaling (Normalization, Standardization). 5️⃣ Overfitting & Underfitting Overfitting – Model learns noise, performs well on training but poorly on test data. Underfitting – Model is too simple and fails to capture patterns. Solution: Regularization (L1, L2), Hyperparameter Tuning. 6️⃣ Ensemble Learning Combining multiple models to improve performance. Bagging (Random Forest) Boosting (XGBoost, Gradient Boosting, AdaBoost) 7️⃣ Deep Learning Basics Neural Networks (ANN, CNN, RNN). Activation Functions (ReLU, Sigmoid, Tanh). Backpropagation & Gradient Descent. 8️⃣ Model Deployment Deploy models using Flask, FastAPI, or Streamlit. Model versioning with MLflow. Cloud deployment (AWS SageMaker, Google Vertex AI). Join our WhatsApp channel: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D

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INTERVIEW CHEATSHEET

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🧿 Essential React Hooks Part 2

Each hook addresses specific performance, state management, or accessibility needs within React components, allowing for efficient and organized code structure.

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🧿 Essential React Hooks Part 1

Each hook addresses specific performance, state management, or accessibility needs within React components, allowing for efficient and organized code structure.

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𝟱 𝗙𝗥𝗘𝗘 𝗣𝘆𝘁𝗵𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀 𝗯𝘆 𝗛𝗮𝗿𝘃𝗮𝗿𝗱, 𝗜𝗕𝗠, 𝗨𝗱𝗮𝗰𝗶𝘁𝘆 & 𝗠𝗼𝗿𝗲😍 Looking to learn Python from scratch—without spending a rupee? 💻 Offered by trusted platforms like Harvard University, IBM, Udacity, freeCodeCamp, and OpenClassrooms, each course is self-paced, easy to follow, and includes a certificate of completion🔥👨‍🎓 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3HNeyBQ Kickstart your career✅️

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🔰 How Python Works?

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𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗙𝗥𝗘𝗘 𝗗𝗲𝗺𝗼 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 𝗜𝗻 𝗣𝘂𝗻𝗲 😍 📊 “Data Analyst” is one of the hottest careers in tech — and guess what? NO coding needed! Learn Data Analytics in Pune with Hands-on Training, Industry Projects, and 100% Placement Assistance. 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝗲𝘀 :- - 100% Placement Assistance - 500+ Hiring Partners - Weekly Hiring Drives 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:- https://pdlink.in/45p4GrC Location:- Acciojob Skill Centre ,Baner, Pune

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Theoretical Questions for Coding Interviews on Basic Data Structures 1. What is a Data Structure? A data structure is a way of organizing and storing data so that it can be accessed and modified efficiently. Common data structures include arrays, linked lists, stacks, queues, and trees. 2. What is an Array? An array is a collection of elements, each identified by an index. It has a fixed size and stores elements of the same type in contiguous memory locations. 3. What is a Linked List? A linked list is a linear data structure where elements (nodes) are stored non-contiguously. Each node contains a value and a reference (or link) to the next node. Unlike arrays, linked lists can grow dynamically. 4. What is a Stack? A stack is a linear data structure that follows the Last In, First Out (LIFO) principle. The most recently added element is the first one to be removed. Common operations include push (add an element) and pop (remove an element). 5. What is a Queue? A queue is a linear data structure that follows the First In, First Out (FIFO) principle. The first element added is the first one to be removed. Common operations include enqueue (add an element) and dequeue (remove an element). 6. What is a Binary Tree? A binary tree is a hierarchical data structure where each node has at most two children, usually referred to as the left and right child. It is used for efficient searching and sorting. 7. What is the difference between an array and a linked list? Array: Fixed size, elements stored in contiguous memory. Linked List: Dynamic size, elements stored non-contiguously, each node points to the next. 8. What is the time complexity for accessing an element in an array vs. a linked list? Array: O(1) for direct access by index. Linked List: O(n) for access, as you must traverse the list from the start to find an element. 9. What is the time complexity for inserting or deleting an element in an array vs. a linked list? Array: Insertion/Deletion at the end: O(1). Insertion/Deletion at the beginning or middle: O(n) because elements must be shifted. Linked List: Insertion/Deletion at the beginning: O(1). Insertion/Deletion in the middle or end: O(n), as you need to traverse the list. 10. What is a HashMap (or Dictionary)? A HashMap is a data structure that stores key-value pairs. It allows efficient lookups, insertions, and deletions using a hash function to map keys to values. Average time complexity for these operations is O(1). Coding interview: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X

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𝟰 𝗙𝗥𝗘𝗘 𝗛𝗮𝗿𝘃𝗮𝗿𝗱 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀 𝗶𝗻 𝗧𝗲𝗰𝗵 (𝗡𝗼 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗡𝗲𝗲𝗱𝗲𝗱!)😍 Dreaming of learning from Harvard — without spending a rupee?💰 You’re in luck! These 4 beginner-friendly courses from Harvard University are completely free, self-paced, & beginner-approved👨‍🎓📌 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/44pDCYd Taught by world-class professors!✅️

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I’ve never met an awesome software developer who: - Thought learning new frameworks was a waste. - Avoided refactoring because “it already works.” - Avoided debugging because it was frustrating. - Never deleted code they once proudly wrote. - Never pushed code that broke in production. - Stuck to one programming language forever. - Stopped learning after getting their first job. - Didn’t rewrite their code later. - Only worked on projects that felt safe. - Refused to ask questions when stuck. Great developers aren’t perfect. They take risks. They make mistakes. They debug endlessly. They make wrong estimates. But during all that, They learn. And that’s exactly why they grow. Keep that in mind

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SQL Joins ✅

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𝗧𝗼𝗽 𝟱 𝗪𝗲𝗯𝘀𝗶𝘁𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗝𝗮𝘃𝗮𝗦𝗰𝗿𝗶𝗽𝘁 𝗶𝗻 𝟮𝟬𝟮𝟱😍 Learning JavaScript doesn’t have to be boring anymore!💫 If endless tutorials make your eyes glaze over, we’ve got just the thing — these super fun & interactive platforms turn learning JavaScript into a game👨‍💻 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3T4yYbP Perfect for daily practice, weekend sprints, or anyone who learns better with hands-on interaction!9✅️

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SQL CHEAT SHEET👩‍💻 Here is a quick cheat sheet of some of the most essential SQL commands: SELECT - Retrieves data from a database UPDATE - Updates existing data in a database DELETE - Removes data from a database INSERT - Adds data to a database CREATE - Creates an object such as a database or table ALTER - Modifies an existing object in a database DROP -Deletes an entire table or database ORDER BY - Sorts the selected data in an ascending or descending order WHERE – Condition used to filter a specific set of records from the database GROUP BY - Groups a set of data by a common parameter HAVING - Allows the use of aggregate functions within the query JOIN - Joins two or more tables together to retrieve data INDEX - Creates an index on a table, to speed up search times.

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