Code With MEMO

It's first day

This How image process.

this it the roadmap that I expect to cover in the first month. I said 14 day challenge: three days in a week. this is the roadmap: https://docs.google.com/document/d/1ZaX8Pb8BMajH9Vv2mhQSk2bws2nH_PoJnw7kqZ5tAZo/edit?tab=t.0

Get Ready for Our Some week AI Journey. I hope you are doing well in python. before proceed to start AI, let's review basics of python, especially related with data science and AI. python for data science

The challenge maybe problems, I give you short notes, algorithm , maybe code. Finally we will do best project. Share my channel if you can!

Hello Memo fam. I thought to give challenges for you everyday, related with AI(ML). Stay with me🤗 We will start tomorrow. @codewithmemo @codewithmemo

📊 Healthcare Risk Factors Dataset 📝 Description: This dataset contains 30,000 records and 20 features related to individuals’ health conditions, along with some noisy/random columns. Medical Condition: Reported health condition (e.g., Diabetes, Hypertension, Asthma, Obesity, Healthy). 📥 Download: • Size: Size not specified • Direct API: Download Link 📊 Stats: • Files: 1 • Downloads: 88 📓 Popular Notebooks: 1. /alicansah1n/medicalconditionclassification-rf-lr-dt-knn-gnb 2. /esraamohamed2003/healthcare-risk-factors-dataset-visualization-task 3. /renjiabarai/medical-condition-prediction 🔗 Powered by @datasets1

Image processing makes me so tired, even my computer looks sleepy😭😭 .now I sleep with my PC for a long time🥲,but I still have high motivation. I just tell myself : no pain, no gain😂.

📅 Nexus Batch 4 Registration Opens November 1!

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The computer and Lazy Programmer Programmer : Computer, run the code. 💻: It has 43 errors. programmer: Ignore them. 💻: I can’t ignore 43 crimes against logic. programmer: I’m debugging tomorrow. 💻: Then I’m crashing today.

In Python, lists are versatile mutable sequences with built-in methods for adding, removing, searching, sorting, and more—covering all common scenarios like dynamic data manipulation, queues, or stacks. Below is a complete breakdown of all list methods, each with syntax, an example, and output, plus key built-in functions for comprehensive use. 📚 Adding Elements ⦁ append(x): Adds a single element to the end.

  lst = [1, 2]
  lst.append(3)
  print(lst)  # Output: [1, 2, 3]
  

⦁ extend(iterable): Adds all elements from an iterable to the end.

  lst = [1, 2]
  lst.extend([3, 4])
  print(lst)  # Output: [1, 2, 3, 4]
  

⦁ insert(i, x): Inserts x at index i (shifts elements right).

  lst = [1, 3]
  lst.insert(1, 2)
  print(lst)  # Output: [1, 2, 3]
  

📚 Removing Elements ⦁ remove(x): Removes the first occurrence of x (raises ValueError if not found).

  lst = [1, 2, 2]
  lst.remove(2)
  print(lst)  # Output: [1, 2]
  

⦁ pop(i=-1): Removes and returns the element at index i (default: last).

  lst = [1, 2, 3]
  item = lst.pop(1)
  print(item, lst)  # Output: 2 [1, 3]
  

⦁ clear(): Removes all elements.

  lst = [1, 2, 3]
  lst.clear()
  print(lst)  # Output: []
  

📚 Searching and Counting ⦁ count(x): Returns the number of occurrences of x.

  lst = [1, 2, 2, 3]
  print(lst.count(2))  # Output: 2
  

⦁ index(x[, start[, end]]): Returns the lowest index of x in the slice (raises ValueError if not found).

  lst = [1, 2, 3, 2]
  print(lst.index(2))  # Output: 1
  

📚 Ordering and Copying ⦁ sort(key=None, reverse=False): Sorts the list in place (ascending by default; stable sort).

  lst = [3, 1, 2]
  lst.sort()
  print(lst)  # Output: [1, 2, 3]
  

⦁ reverse(): Reverses the elements in place.

  lst = [1, 2, 3]
  lst.reverse()
  print(lst)  # Output: [3, 2, 1]
  

⦁ copy(): Returns a shallow copy of the list.

  lst = [1, 2]
  new_lst = lst.copy()
  print(new_lst)  # Output: [1, 2]
  

📚 Built-in Functions for Lists (Common Cases) ⦁ len(lst): Returns the number of elements.

  lst = [1, 2, 3]
  print(len(lst))  # Output: 3
  

⦁ min(lst): Returns the smallest element (raises ValueError if empty).

  lst = [3, 1, 2]
  print(min(lst))  # Output: 1
  

⦁ max(lst): Returns the largest element.

  lst = [3, 1, 2]
  print(max(lst))  # Output: 3
  

⦁ sum(lst[, start=0]): Sums the elements (start adds an offset).

  lst = [1, 2, 3]
  print(sum(lst))  # Output: 6
  

⦁ sorted(lst, key=None, reverse=False): Returns a new sorted list (non-destructive).

  lst = [3, 1, 2]
  print(sorted(lst))  # Output: [1, 2, 3]
  

These cover all standard operations (O(1) for append/pop from end, O(n) for most others). Use slicing lst[start:end:step] for advanced extraction, like lst[1:3] outputs ``. #python #lists #datastructures #methods #examples #programming ⭐ @DataScience4

🎉 Congratulations to everyone accepted into DSA Team Round 3! For those who haven’t been added to the new group yet, please check your privacy settings and contact @ISHubAAU_Support for assistance. 🗓 Orientation Session: 📅 Today, 8:00 PM (2 LT) This session will walk you through what to expect, the roadmap ahead, and how we’ll grow together as a community. Let’s build. Let’s solve. Let’s rise. Solve together, grow together. 📢 Stay connected: Telegram|LinkedIn|YouTube | Tiktok |