Course Content
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Day-17: Complete EDA on Google PlayStore Apps
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Day-25: Quiz Time, Data Visualization-4
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Day-27: Data Scaling/Normalization/standardization and Encoding
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Day-30: NumPy (Part-3)
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Day-31: NumPy (Part-4)
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Day-32a: NumPy (Part-5)
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Day-32b: Data Preprocessing / Data Wrangling
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Day-37: Algebra in Data Science
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Day-56: Statistics for Data Science (Part-5)
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Day-69: Machine Learning (Part-3)
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Day-75: Machine Learning (Part-9)
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Day-81: Machine Learning (Part-15)-Evaluation Metrics
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Day-82: Machine Learning (Part-16)-Metrics for Classification
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Day-85: Machine Learning (Part-19)
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Day-89: Machine Learning (Part-23)
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Day-91: Machine Learning (Part-25)
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Day-93: Machine Learning (Part-27)
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Day-117: Deep Learning (Part-14)-Complete CNN Project
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Day-119: Deep Learning (Part-16)-Natural Language Processing (NLP)
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Day-121: Time Series Analysis (Part-1)
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Day-123: Time Series Analysis (Part-3)
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Day-128: Time Series Analysis (Part-8): Complete Project
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Day-129: git & GitHub Crash Course
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Day-131: Improving Machine/Deep Learning Model’s Performance
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Day-133: Transfer Learning and Pre-trained Models (Part-2)
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Day-134 Transfer Learning and Pre-trained Models (Part-3)
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Day-137: Generative AI (Part-3)
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Day-139: Generative AI (Part-5)-Tensorboard
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Day-145: Streamlit for webapp development and deployment (Part-1)
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Day-146: Streamlit for webapp development and deployment (Part-2)
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Day-147: Streamlit for webapp development and deployment (Part-3)
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Day-148: Streamlit for webapp development and deployment (Part-4)
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Day-149: Streamlit for webapp development and deployment (Part-5)
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Day-150: Streamlit for webapp development and deployment (Part-6)
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Day-151: Streamlit for webapp development and deployment (Part-7)
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Day-152: Streamlit for webapp development and deployment (Part-8)
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Day-153: Streamlit for webapp development and deployment (Part-9)
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Day-154: Streamlit for webapp development and deployment (Part-10)
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Day-155: Streamlit for webapp development and deployment (Part-11)
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Day-156: Streamlit for webapp development and deployment (Part-12)
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Day-157: Streamlit for webapp development and deployment (Part-13)
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How to Earn using Data Science and AI skills
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Day-160: Flask for web app development (Part-3)
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Day-161: Flask for web app development (Part-4)
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Day-162: Flask for web app development (Part-5)
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Day-163: Flask for web app development (Part-6)
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Day-164: Flask for web app development (Part-7)
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Day-165: Flask for web app deployment (Part-8)
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Day-167: FastAPI (Part-2)
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Day-168: FastAPI (Part-3)
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Day-169: FastAPI (Part-4)
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Day-170: FastAPI (Part-5)
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Day-171: FastAPI (Part-6)
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Day-174: FastAPI (Part-9)
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Six months of AI and Data Science Mentorship Program
About Lesson

Important Things to know before the lecture:

In the Gaussian elimination and its extended versions method for solving systems of linear equations, specific row operations are used to transform the matrix into an upper triangular form or row echelon form. These operations are fundamental to the process and are designed to preserve the system’s solutions.

Permissible Row Operations

  1. Swapping Rows: You can interchange two rows. This operation does not change the solution set of the system.

  2. Multiplying a Row by a Non-zero Scalar: Any row can be multiplied by a non-zero constant. This operation changes the scale of the equation but not its solutions.

  3. Adding a Multiple of One Row to Another: You can add or subtract a multiple of one row to another row. This operation is used to create zeros in specific positions under the pivot elements.

Operations Not Permissible

  • Multiplying or Adding Rows with Columns: Operations involving both rows and columns simultaneously are not allowed, as they would change the nature of the system.

  • Multiplying a Row by Zero: This operation is not allowed as it leads to loss of information from the equation, potentially changing the solution set.

  • Changing the Number of Rows or Columns: Any operation that alters the dimensions of the matrix (like adding or removing a row or column) is not permissible, as it would change the underlying system of equations.

Importance of Following Permissible Operations

The key purpose of these operations in Gaussian elimination is to systematically simplify the matrix while ensuring that the transformed matrix represents a system of equations equivalent to the original. This means that the operations should neither alter the solution set nor introduce any new solutions. Adhering to the permissible operations guarantees that the integrity of the system is maintained throughout the process.

Join the conversation
Muhammad_Faizan 4 weeks ago
DONE
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tayyab Ali 6 months ago
I have done this lecture.
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Sibtain Ali 6 months ago
Done this video.
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kashan malik 6 months ago
DONE
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Shahid Umar 7 months ago
In this lecture, I knew that the Gauss-Jordon method is actually the extension of the Gaussian Elimination method.
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