Coding Projects
Channel specialized for advanced concepts and projects to master: * Python programming * Web development * Java programming * Artificial Intelligence * Machine Learning Managed by: @love_data
Ko'proq ko'rsatish📈 Telegram kanali Coding Projects analitikasi
Coding Projects (@programming_experts) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 67 932 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 1 914-o'rinni va Hindiston mintaqasida 4 746-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 67 932 obunachiga ega bo‘ldi.
28 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 157 ga, so‘nggi 24 soatda esa -8 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 3.29% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.04% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 236 marta ko‘riladi; birinchi sutkada odatda 709 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 5 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent |--, algorithm, array, framework, javascript kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Channel specialized for advanced concepts and projects to master:
* Python programming
* Web development
* Java programming
* Artificial Intelligence
* Machine Learning
Managed by: @love_data”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 29 Oktabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
Why type emails when Python can do it for you? Work smarter, not harder... unless you’re debugging. 😅💻
DISTINCT keyword in a SELECT statement to retrieve unique records. For example: SELECT DISTINCT column1, column2 FROM table;
5. Question: What is a subquery in SQL?
Answer: A subquery is a query nested inside another query. It can be used to retrieve data that will be used in the main query as a condition to further restrict the data to be retrieved.
6. Question: Explain the purpose of the GROUP BY clause.
Answer: The GROUP BY clause is used to group rows that have the same values in specified columns into summary rows, like when using aggregate functions such as COUNT, SUM, AVG, etc.
7. Question: How can you add a new record to a table?
Answer: Use the INSERT INTO statement. For example: INSERT INTO table_name (column1, column2) VALUES (value1, value2);
8. Question: What is the purpose of the HAVING clause?
Answer: The HAVING clause is used in combination with the GROUP BY clause to filter the results of aggregate functions based on a specified condition.
9. Question: Explain the concept of normalization in databases.
Answer: Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves breaking down tables into smaller, related tables.
10. Question: How do you update data in a table in SQL?
Answer: Use the UPDATE statement to modify existing records in a table. For example: UPDATE table_name SET column1 = value1 WHERE condition;
Here is an amazing resources to learn & practice SQL: https://bit.ly/3FxxKPz
Share with credits: https://t.me/sqlspecialist
Hope it helps :)scipy.stats, statsmodels, pandas
Visualization: seaborn, matplotlib
💡 Quick tip: Use these formulas to crush interviews and build solid ML foundations!
💬 Tap ❤️ for moredef bubble_sort(arr):
for i in range(len(arr)):
for j in range(len(arr)-i-1):
if arr[j] > arr[j+1]:
arr[j], arr[j+1] = arr[j+1], arr[j]
*C++*void bubbleSort(int arr[], int n) {
for(int i=0; i<n-1; i++)
for(int j=0; j<n-i-1; j++)
if(arr[j] > arr[j+1])
swap(arr[j], arr[j+1]);
}
*Java*void bubbleSort(int[] arr) {
for(int i = 0; i < arr.length - 1; i++)
for(int j = 0; j < arr.length - i - 1; j++)
if(arr[j] > arr[j+1]) {
int temp = arr[j]; arr[j] = arr[j+1]; arr[j+1] = temp;
}
}
🟡 2. Binary Search – Searching Algorithm
👉 Efficiently searches a sorted array in O(log n) time.
*Python*def binary_search(arr, target):
low, high = 0, len(arr)-1
while low <= high:
mid = (low + high) // 2
if arr[mid] == target: return mid
elif arr[mid] < target: low = mid + 1
else: high = mid - 1
return -1
🟠 3. Recursion – Factorial Example
👉 Function calls itself to solve smaller subproblems.
*C++*int factorial(int n) {
if(n == 0) return 1;
return n * factorial(n - 1);
}
🔵 4. Dynamic Programming – Fibonacci (Bottom-Up)
👉 Stores previous results to avoid repeated work.
*Python*def fib(n):
dp = [0, 1]
for i in range(2, n+1):
dp.append(dp[i-1] + dp[i-2])
return dp[n]
🟣 5. Sliding Window – Max Sum Subarray of Size K
👉 Finds max sum in a subarray of fixed length in O(n) time.
*Java*int maxSum(int[] arr, int k) {
int sum = 0, max = 0;
for(int i = 0; i < k; i++) sum += arr[i];
max = sum;
for(int i = k; i < arr.length; i++) {
sum += arr[i] - arr[i - k];
if(sum > max) max = sum;
}
return max;
}
🧠 6. BFS (Breadth-First Search) – Graph Traversal
👉 Explores all neighbors before going deeper.
*Python*from collections import deque
def bfs(graph, start):
visited = set([start])
queue = deque([start])
while queue:
node = queue.popleft()
print(node)
for neighbor in graph[node]:
if neighbor not in visited:
visited.add(neighbor)
queue.append(neighbor)
👍 Tap ❤️ for more! #coding #algorithms #interviews #programming #datastructures
Note: I've addedaround code snippets to format them correctly in Telegram.
