Expert Lecture on Python

 Unit no 1 Problem Solving, Programming and Python Programming

General Problem-Solving Concepts: 

Problem Solving in everyday life.

Having no problems is the

 biggest problem of all.

 — Taiichi Ohno

What is Problem?
A problem is a situation that is unsatisfactory and causes difficulties for people and needs to be dealt with or solved.

For Example, let's See what is the Alberto's Problem? I like Problem Alway's

Problem Solving Steps:

The problem-solving process typically includes the following steps:

1. Identify the issue: Recognize the problem that needs to be solved.

2. Analyze the situation: Examine the issue in depth, gather all relevant information, and consider any limitations or constraints that may be present.

3. Generate potential solutions: Brainstorm a list of possible solutions to the issue, without immediately judging or evaluating them.

4. Evaluate options: Weigh the pros and cons of each potential solution, considering factors such as feasibility, effectiveness, and potential risks.

5. Select the best solution: Choose the option that best addresses the problem and aligns with your objectives.

6. Implement the solution: Put the selected solution into action and monitor the results to ensure it resolves the issue.

7. Review and learn: Reflect on the problem-solving process, identify any improvements or adjustments that can be made, and apply these learnings to future situations.

Program Design Tools: Algorithm, Flowchart, Pseudo-codes.

Data Structures

Basics of Python Programming:

1. Features of Python: Click here to learn features

2. History of Python: Click here to learn more

3. Literal Constants: click here to learn more.

4. Keyword (reserved word), Variables, and Identifiers: Click here to learn more

 For details about variables click here

5. Data Types: click here to learn more

6. Input Operation in Python: Click here to Learn More

7. Indentation in Python: Click here to learn more..

8. Operators in Python: Click here to learn more

9. Expressions in python: Click here

 

Applications of Deep Learning

 Q. Explain common architectural principles of deep networks.

 Q. List the Application of Deep Learning.

Working-Application of DL

Q. What is the Learning representation of Data? or Feature learning or Representation Learning?

Q. How does deep learning work in three figures explain with an example.

What is Deep Learning ?

Write a short note on the History of Deep Learning.

Define Deep Learning. Explain it's Pros and cons.

DataTypes

 Each variable in C has an associated data type. It specifies the type of data that the variable can store like integer, character, floating, double, etc. Each data type requires different amounts of memory and has some specific operations which can be performed over it. The data type is a collection of data with values having fixed values, meaning as well as its

 What is Machine Learning?

 Why should we learn Machine Learning?

How does Machine Learning Work?

Explain types of Machine Learning?

Difference between supervised-unsupervised

What is Bias?

What is Variance?

What is underfitting?

What is Overfitting?

What is  Best fitting or idle Scenario?

What are Parameters?

What are Hyperparameters?

Write short note on: Full Training Pipeline.

Write short note on: under/over fitting Regularization.

Explain various Limitation of Machine Learning