Data Science & Machine Learning
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Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data
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网络:📈 Telegram 频道 Data Science & Machine Learning 的分析概览
频道 Data Science & Machine Learning (@datasciencefun) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 76 468 名订阅者，在 教育 类别中位列第 2 066，并在 印度 地区排名第 4 109 位。
📊 受众指标与增长动态
自 невідомо 创建以来，项目保持高速增长，吸引了 76 468 名订阅者。
根据 13 七月, 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 721，过去 24 小时变化为 38，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 2.82%。内容发布后 24 小时内通常能获得 1.30% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 2 156 次浏览，首日通常累积 992 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 3。
- 主题关注点： 内容集中在 learning, accuracy, distribution, panda, dataset 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：
“Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free
For collaborations: @love_data”
凭借高频更新（最新数据采集于 14 七月, 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 教育 类别中的关键影响点。
76 468
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| 日期 | 订阅者增长 | 提及 | 频道 | |
| 14 七月 | +30 | |||
| 13 七月 | +38 | |||
| 12 七月 | +19 | |||
| 11 七月 | +13 | |||
| 10 七月 | +7 | |||
| 09 七月 | +43 | |||
| 08 七月 | +29 | |||
| 07 七月 | +12 | |||
| 06 七月 | +65 | |||
| 05 七月 | +17 | |||
| 04 七月 | +33 | |||
| 03 七月 | +51 | |||
| 02 七月 | +25 | |||
| 01 七月 | +31 |
频道帖子
if age >= 18:
print("Eligible")if age >= 18:
print("Eligible")if age >= 18:
print("Eligible")prediction = 0.82
if prediction >= 0.5:
print("Spam Email")
else:
print("Not Spam")| 2 | 🚀 Data Science Roadmap 2026
📘 Phase 1: Programming Fundamentals
🐍 Topic 4: Python Conditional Statements (if, elif, else)
Welcome back! 👋
In the previous lesson, you learned how to take input from users and display output. Now it's time to learn how Python makes decisions.
Conditional statements allow a program to execute different blocks of code based on whether a condition is True or False.
They are one of the most important concepts in Python and are used extensively in Data Science, Machine Learning, and real-world applications.
🔹 1. What are Conditional Statements?
Conditional statements help Python decide which code should run based on a condition.
Think of it like making everyday decisions:
• If it's raining → Carry an umbrella.
• Else → Wear sunglasses.
Similarly, Python checks a condition and decides what to execute.
🔹 2. The "if" Statement
The "if" statement executes a block of code only if the condition is True.
Syntax
if condition:
# Code to execute
Example
age = 20
if age >= 18:
print("Eligible to vote")
Output
Eligible to vote
🔹 3. The "if...else" Statement
Use "else" when you want to execute another block if the condition is False.
Example
age = 16
if age >= 18:
print("Eligible to vote")
else:
print("Not eligible to vote")
Output
Not eligible to vote
🔹 4. The "if...elif...else" Statement ⭐
Use "elif" when you need to check multiple conditions.
Example
marks = 85
if marks >= 90:
print("Grade A")
elif marks >= 75:
print("Grade B")
elif marks >= 60:
print("Grade C")
else:
print("Grade D")
Output
Grade B
Python checks conditions from top to bottom and executes the first condition that is True.
🔹 5. Nested "if" Statements
You can place one "if" statement inside another.
Example
age = 25
citizen = True
if age >= 18:
if citizen:
print("Eligible to vote")
Output
Eligible to vote
🔹 6. Using Logical Operators
Conditional statements often use logical operators.
"and"
age = 25
if age >= 18 and age <= 60:
print("Working Age")
"or"
marks = 35
if marks >= 40 or marks == 35:
print("Eligible for Grace Marks")
"not"
is_holiday = False
if not is_holiday:
print("Go to Office")
🔹 7. Checking Multiple Conditions
salary = 60000
experience = 4
if salary > 50000 and experience >= 3:
print("Eligible for Promotion")
else:
print("Not Eligible")
🔹 8. Ternary Operator ⭐
A shorter way to write an "if...else" statement.
Syntax
value_if_true if condition else value_if_false
Example
age = 20
status = "Adult" if age >= 18 else "Minor"
print(status)
Output
Adult
🔹 9. Real-World Example
temperature = 38
if temperature > 35:
print("It's a hot day.")
elif temperature >= 20:
print("Weather is pleasant.")
else:
print("It's cold.")
🔹 10. Common Mistakes
❌ Missing Colon
if age >= 18
print("Eligible")
This gives a SyntaxError.
Correct: | 1 108 |
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2. Stay teachable
3. Give unselfishly
4. Read and write more
5. Show up on time
6. Quit complaining
7. Develop good manners
8. Be humble and show gratitude
9. Be kind and generous
10. Surround yourself with smarter people | 1 398 |
| 5 | Which is the recommended way to format strings in modern Python? | 1 594 |
| 6 | Which function should you use to convert user input into an integer? | 1 502 |
| 7 | What data type does the input() function return by default? | 1 420 |
| 8 | Which function is used to take input from the user in Python? | 1 344 |
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| 11 | num1 = int(input("Enter first number: "))
num2 = int(input("Enter second number: "))
print(num1 + num2)
Output:
30
🔹 12. Real-World Example
salary = float(input("Enter your monthly salary: "))
annual_salary = salary * 12
print(f"Your annual salary is {annual_salary}")
🎯 Practice Questions
1. Take your name as input and print a welcome message.
2. Take two integers as input and print their sum.
3. Take a student's marks as input and print them using an f-string.
4. Take the radius of a circle as input and calculate the area.
5. Take your birth year as input and calculate your approximate age.
🎯 Key Takeaways
✅ Use print() to display output
✅ Use input() to accept user input
✅ input() always returns a string
✅ Convert input using int() or float() when needed
✅ Use f-strings for clean and readable output formatting
Double Tap ❤️ For More | 1 643 |
| 12 | 🚀 Data Science Roadmap 2026
📘 Phase 1: Programming Fundamentals
🐍 Topic 3: Python Input & Output
In the previous lesson, you learned about Python Operators. Now it's time to learn how Python interacts with users by taking input and displaying output.
Input and Output (I/O) are fundamental concepts because almost every real-world program accepts input, processes it, and produces meaningful output.
🔹 1. What is Input & Output?
A Python program generally follows three steps:
Input → Process → Output
Example:
• User enters two numbers Input
• Python adds them Process
• Sum is displayed Output
🔹 2. Displaying Output
Python uses the print() function to display information on the screen.
Example
print("Hello, Data Science!")
Output
Hello, Data Science!
🔹 3. Printing Variables
You can print variables along with text.
name = "Deepak"
print(name)
Output:
Deepak
Or:
name = "Deepak"
print("Welcome", name)
Output:
Welcome Deepak
🔹 4. Taking User Input
Python uses the input() function to receive input from users.
name = input("Enter your name: ")
print("Hello", name)
Example Output:
Enter your name: Deepak
Hello Deepak
🔹 5. Important Note ⭐
The input() function always returns a string, even if the user enters a number.
age = input("Enter age: ")
print(type(age))
Output:
<class 'str'>
🔹 6. Converting Input to Integer
To perform mathematical operations, convert the input using int().
age = int(input("Enter your age: "))
print(age + 5)
Example:
Enter your age: 25
30
🔹 7. Taking Decimal Input
Use float() for decimal numbers.
price = float(input("Enter price: "))
print(price)
🔹 8. Taking Multiple Inputs
You can take multiple inputs in a single line.
name, city = input("Enter your name and city: ").split()
print(name)
print(city)
Example Input:
Deepak Mumbai
Output:
Deepak
Mumbai
🔹 9. Formatting Output
Using f-Strings ⭐ Recommended
name = "Deepak"
age = 25
print(f"My name is {name} and I am {age} years old.")
Output:
My name is Deepak and I am 25 years old.
Using .format()
name = "Deepak"
print("Welcome {}".format(name))
🔹 10. Example Program
name = input("Enter your name: ")
age = int(input("Enter your age: "))
print(f"Hello {name}")
print(f"Next year you will be {age + 1} years old.")
Example Output:
Enter your name: Deepak
Enter your age: 25
Hello Deepak
Next year you will be 26 years old.
🔹 11. Common Mistake
num1 = input("Enter first number: ")
num2 = input("Enter second number: ")
print(num1 + num2)
Input:
10
20
Output:
1020
Why?
Because both values are strings.
Correct way: | 1 337 |
| 13 |  𝗠𝗮𝘀𝘁𝗲𝗿 𝗧𝗵𝗲𝘀𝗲 𝗛𝗶𝗴𝗵-𝗗𝗲𝗺𝗮𝗻𝗱 𝗦𝗸𝗶𝗹𝗹𝘀 𝘁𝗼 𝗟𝗮𝗻𝗱 𝗛𝗶𝗴𝗵-𝗣𝗮𝘆𝗶𝗻𝗴 𝗝𝗼𝗯𝘀 🔥
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| 14 | Which logical operator returns True only if both conditions are True? | 1 724 |
| 15 | Which operator is used for exponentiation (power) in Python? | 1 680 |
| 16 |  𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗥𝗘𝗘 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀🎓
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| 17 | result = 10 + 5 * 2
print(result)
Output:
20
Multiplication is performed before addition.
Use parentheses to change the order.
result = (10 + 5) * 2
print(result)
Output:
30
🔹 10. Real-World Example
salary = 60000
bonus = 5000
total_salary = salary + bonus
is_high_salary = total_salary > 50000
print(total_salary)
print(is_high_salary)
Output:
65000
True
🎯 Key Takeaways
✅ Operators perform calculations and comparisons.
✅ Arithmetic operators are used for mathematical operations.
✅ Comparison operators return True or False.
✅ Logical operators help combine multiple conditions.
✅ Membership operators check if a value exists in a sequence.
✅ Identity operators check whether two variables refer to the same object.
Double Tap ❤️ For More | 1 700 |
| 18 | 🚀 Data Science Roadmap 2026
📘 Phase 1: Programming Fundamentals
🐍 Topic 2: Python Operators
In the previous lesson, you learned about Variables & Data Types. Now it's time to learn how Python performs calculations, comparisons, and logical operations using operators.
Operators are one of the most fundamental concepts in Python. You'll use them in almost every program, from simple calculations to complex Machine Learning algorithms.
🔹 1. What are Operators?
Operators are special symbols used to perform operations on variables and values.
Example:
a = 10
b = 5
print(a + b)
Output:
15
Here, "+" is an operator that adds two numbers.
🔹 2. Types of Operators in Python
Python has several types of operators:
✅ Arithmetic Operators
✅ Comparison Operators
✅ Assignment Operators
✅ Logical Operators
✅ Membership Operators
✅ Identity Operators
🔹 3. Arithmetic Operators ⭐
Used for mathematical calculations.
Operators:
• ** + Addition**: 10 + 5 = 15
• - Subtraction: 10 - 5 = 5
• ** Multiplication*: 10 * 5 = 50
• / Division: 10 / 5 = 2.0
• // Floor Division: 10 // 3 = 3
• % Modulus (Remainder): 10 % 3 = 1
• ** Exponent: 2 ** 3 = 8
Example:
a = 10
b = 3
print(a + b)
print(a - b)
print(a * b)
print(a / b)
print(a // b)
print(a % b)
print(a ** b)
🔹 4. Comparison Operators ⭐
Used to compare two values. The result is always True or False.
Operators:
• == Equal to
• != Not Equal to
• > Greater than
• < Less than
• >= Greater than or Equal to
• <= Less than or Equal to
Example:
x = 20
y = 10
print(x > y)
print(x == y)
print(x != y)
Output:
True
False
True
🔹 5. Assignment Operators
Used to assign values to variables.
x = 10
x += 5
print(x)
Output:
15
Other assignment operators:
x -= 2
x *= 3
x /= 2
🔹 6. Logical Operators ⭐
Used to combine multiple conditions.
and
Returns True only if both conditions are True.
age = 25
print(age > 18 and age < 30)
Output:
True
or
Returns True if at least one condition is True.
print(age < 18 or age < 30)
Output:
True
not
Reverses the result.
print(not(age > 18))
Output:
False
🔹 7. Membership Operators
Used to check whether a value exists in a sequence.
in
fruits = ["Apple", "Banana", "Mango"]
print("Apple" in fruits)
Output:
True
not in
print("Orange" not in fruits)
Output:
True
🔹 8. Identity Operators
Used to check whether two variables refer to the same object.
is
a = [1, 2]
b = a
print(a is b)
Output:
True
is not
x = [1, 2]
y = [1, 2]
print(x is not y)
Output:
True
🔹 9. Operator Precedence
Python follows the PEMDAS/BODMAS rule while evaluating expressions.
Example: | 1 406 |
| 19 |  𝗔𝗜 𝗶𝗻 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 😍
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Date & Time :- 11th July 2026 , 8:00 PM (IST) | 1 247 |
| 20 |  GigaChat 3.5 Ultra Publicly Released — The New Generation of the Flagship Model
The GigaChat team has released GigaChat 3.5 Ultra as open source—a new 432B model under the MIT license. This is the first open-source hybrid of GatedDeltaNet and MLA scaled to hundreds of billions of parameters, featuring a proprietary training recipe we refined through more than 1,500 experiments. The model has grown in terms of code, mathematics, agent scenarios, and application domains—yet it’s 40% smaller than GigaChat 3.1 Ultra.
What’s inside:
🔘A proprietary hybrid MLA + Gated DeltaNet architecture with a dedicated stabilization framework, without which this hybrid setup would not train reliably at this scale;
🔘 Gated Attention: the model can locally down-weight overly strong signals from the attention layer;
🔘GatedNorm: normalization with an explicit gate that controls signal magnitude across features;
🔘Approximately 4x lower KV cache per token: with the same memory budget, the model can support 2.14x longer context and deliver a 20% throughput increase under load;
🔘Two MTP heads, enabling up to 2.2x faster generation;
🔘FP8 across all training stages with no quality degradation compared with bf16, enabled by custom Triton and CUDA kernels;
🔘A new online RL stage after SFT and DPO.
Results:
🔘 GigaChat-3.5-Ultra-Base outperforms DeepSeek V3.2 Exp Base and DeepSeek V4 Flash Base on average across a set of general, math, and code benchmarks:
🔘 GigaChat-3.5-Ultra-Instruct is comparable to DeepSeek V3.2 in terms of average score, despite having half the size;
🔘 According to the MiniMax-M2.7 LLM judge, the average win rate against GigaChat 3.1 Ultra is 75.9%, and against GPT-5 is 68.7%.
The entire stack — data (our own LLM-filtered Common Crawl, 600+ programming languages in the code), architecture, training methodology, and infrastructure — was built end-to-end by GigaChat team.
➡️ HuggingFace | 1 546 |
