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Progress-Sheet

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Daily Progress Log

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chart


March 14, 2023

Activity Time Spent Things Learned Problem Faced
Problem Solving 3 hrs
  • Reminiscing Stl
  • Time Complexity
  • Comparator Sort
  • 2 Problems from Atcoder
  • 1 Problem from Codeforces
Andrew Ng 0.72 hrs
  • Simplified Loss Function for Logistic Regression
  • Simplified Cost Function
  • Implementation of Cost & Loss Function

Goals for Tomorrow

  • Start Student Performance Project ASAP
  • Stop being a lazy cunt


March 13, 2023

Activity Time Spent Things Learned Problem Faced
Problem Solving 3.4 hrs
  • 3 Problems from Codeforces

    Goals for Tomorrow

    • Start Student Performance Project
    • Finish 3 Andrew Ng videos


    March 12, 2023

    Activity Time Spent Things Learned Problem Faced
    Problem Solving 3.2 hrs
    • 4 Problems from Codeforces

      Goals for Tomorrow

      • Start Student Performance Project
      • Problem solving for at least 3 hrs
      • Finish 3 Andrew Ng videos


      March 11, 2023

      Activity Time Spent Things Learned Problem Faced
      Andrew Ng 1.3 hrs
      • Cost Function for Logistic Regression
      • Logistic Loss Function
      • Reason the squared error loss is not appropriate for logistic regression
        • Logistic loss function

        Goals for Tomorrow

        • Spend at least 3 hrs on problem solving
        • Start student performance project


        March 10, 2023

        Activity Time Spent Things Learned Problem Faced
        Andrew Ng 1.4 hrs
        • Decision Boundary
        • Threshold
        • Decision Boundary Line
        • Non Linear Decision Boundary
        • Plot the decision boundary for a logistic regression model

          Goals for Tomorrow

          • Start doing Student Performance project
          • Follow mentors guideline


          March 9, 2023

          Activity Time Spent Things Learned Problem Faced
          Andrew Ng 2.6 hrs
          • Assignment on implementating Linear Regression (univariate)
          • Introduction to Classification
          • Binary Classification
          • Sigmoid Function / Logistic Function
          • Logistic Regression
          • Interpretation of Logistic Regression
          • Implementating Logistic Regression Model using Linear Regressin & Sigmoid Function
          • np_c function

            Goals for Tomorrow

            • Wake up at 7 am
            • Do more activities
            • Looking for more Projects to do
            • Explore how Chess can be played using ML


            March 8, 2023

            Activity Time Spent Things Learned Problem Faced
            Machine Learning Project 4.3 hrs
            • House Price Preditction 3
            • Feature Scaling with Z-score Normalization
            • Relation between Features and Targets
            • Linear Regression using Scikit-Learn
            • Cost comparison between Scratch implementation vs Sk-learn’s LinearRegression model
              • Implemented function and Scikit-Learn’s Linear model’s overall cost is pretty similar. But both have huge total cost.
              Andrew Ng 1.5 hrs
              • Feature Engineering
              • Using Intution to design new features out of originals
              • Polynomial Regression
              • Importance of feature scaling in Feature Engineering
                • Feature Engineering Lab implementation went over my head

                Goals for Tomorrow

                • Start the week 3 of Andrew Ng
                • Refine the project a little bit.


                March 7, 2023

                Activity Time Spent Things Learned Problem Faced
                Andrew Ng 1.5 hrs
                • Run Gradient Descent on a data set with multiple Features
                • Explore the impact of the Learning Rate (alpha)
                • Feature Scaling using Z-score Normalization

                  Goals for Tomorrow

                  • Complete the House Price Prediction project and adding context to it


                  March 6, 2023

                  Activity Time Spent Things Learned Problem Faced
                  Machine Learing Project 1.8 hrs
                  • House Price Prediction 2
                  • Normalization by dividing Max on Train & Test data
                  • Dropping (deleting) data rows consisting null values
                  • Learning Rate tweaking for best outcome
                  • Plotting the convergence of Cost Function
                  • Cost computing on Test data
                  • Debugging Multiple Linear Regression
                    • Normalized both inputs and targets to reduce the cost
                    Mid Preparation Ꝏ

                    Goals for Tomorrow

                    • Getting over with the exam and resume the projec


                    March 5, 2023

                    Activity Time Spent Things Learned Problem Faced
                    Mid Preparation Ꝏ

                    Goals for Tomorrow

                    • Getting over with the exam and resume the project


                    March 4, 2023

                    Activity Time Spent Things Learned Problem Faced
                    Andrew Ng 1.6 hrs
                    • Feature Scaling
                    • Importance of Feature Scaling
                    • Divide by Maximum scaling
                    • Mean Normalization
                    • Z-Score Normalizaion
                    • Standard Deviation
                    • Acceptable Feature value ranges
                    • Check Gradient Descent for Converge
                    • Autometic Converge test
                    • When to Declare Convergence
                    • Choosing the Learning Rate
                    • Identify the problems with Gradient Descent
                    • Debugging Gradient Descent
                      Mid Preparation Ꝏ

                      Goals for Tomorrow

                      • Continue Mid & Progress as much as I can.


                      March 3, 2023

                      Activity Time Spent Things Learned Problem Faced
                      Mid Preparation Ꝏ

                      Goals for Tomorrow

                      • Continue Mid & Progress as much as I can.


                      March 2, 2023

                      Activity Time Spent Things Learned Problem Faced
                      Machine Learning Project 2.7 hrs
                      • House Price Prediction part 1
                      • Missing / null value Checking
                      • Replacing missing values with Mean
                      • Gradient Function Implementation
                      • Gradient Descent Implementation
                      • Multiple Linear Regression
                        • Learning Rate issue
                        • Predicted price is not even close
                        • Accuracy_score function not working

                        Goals for Tomorrow

                        • Continue Mid & Progress as much as I can.


                        March 1, 2023

                        Activity Time Spent Things Learned Problem Faced
                        Andrew Ng 2.5 hrs
                        • Reminiscing previous Labs & Quiz
                        • Gradient Descent for more than one Features
                        • An alternative to Gradient Descent, Normal Euation Method
                        • Cost Computing for Multiple Variables
                        • Implementation of Multiple Linear Regression
                          • Predicted cost of the model is yet to be efficient
                          Mid Preparation Ꝏ

                          Goals for Tomorrow

                          • Continue Mid & Progress as much as I can.


                          February 28, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Progress Sheet 0.6 hrs
                          • Extract total time spent over different topic using Formulas
                          • Inserting Charts inside google sheets
                          Andrew Ng 1.6 hrs
                          • Vectorization
                          • NumPy For Vectorization
                          • Vectors
                          • Dot Product using NumPy
                          • Vectorization vs For Loop (Speed Test)
                          • Matrix Indexing & Slicing
                          Mid Preparation Ꝏ

                          Goals for Tomorrow

                          • Continue Mid & Progress as much as I can.


                          February 27, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Andrew Ng 1.1 hrs
                          • Cost Function Implementation
                          • Gradient Descent Implementation for one Featur
                          • Multiple Linear Regression / Linear Regression with Multiple Features

                          Goals for Tomorrow

                          • Continue Mid & Progress as much as I can.
                          • Finish vectorization & Gradient Descent for Multiple Linear Regression.


                          February 26, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Mid Preparation Ꝏ

                          Goals for Tomorrow

                          • Continue Mid & Progress as much as I can.


                          February 24, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Model Deployment 2 hrs
                          • Introduction to the Deployment of Machine Learning Model
                          • Exporting the Model from Jupyter Notebook as .pkl file
                          • Deploy it on Local Machine
                          • Deploying a Model on GitHub Pages
                          Mid Preparation Ꝏ

                          Goals for Tomorrow

                          • Continue Mid & Progress as much as I can.

                          February 24, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Mid Preparation Ꝏ

                          Goals for Tomorrow

                          • Continue Mid & Progress as much as I can.


                          February 23, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Andrew Ng 1.2 hrs
                          • Gradient Descent Intuition
                          • Learning Rate
                          • Choosing better Learning Rate
                          • Local Minimum
                          • Global Minimum
                          • Reaching Local Minimum
                          • Convex Function
                          Mid Preparation Ꝏ

                          Goals for Tomorrow

                          • Continue Mid & Progress as much as I can.


                          February 22, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Andrew Ng 2.4 hrs
                          • Cost Function models in 3d
                          • Contour Plot of Cost Function
                          • Finding Minimum value of cost function
                          • Inital guess effect of the parameters of the cost function

                          Goals for Tomorrow

                          • Simply avoid Phone
                          • Start Module 2 of Andrew Ng and go through it fast


                          February 21, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Machine Learning Project 1.4 hrs
                          • Rock vs Mine Prediction part 2
                          • Train and Test data splitting
                          • Training LogisticRegression Model
                          • Checking a Model’s accuracy
                          • Making of a Predictive System
                          • Logictic Regression Model Theory
                          Mid Preparation Ꝏ

                          Goals for Tomorrow

                          • Finish the Module 1 of Andrew Ng
                          • Explore beginner projects to do later


                          February 20, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Python Data-camp 1.4 hrs
                          • Pandas
                            • DataFrame
                          • CSV File reading
                          • loc
                          • iloc
                          Machine Learning Project 0.75 hrs
                          • Rock vs Mine Prediction
                          • Working with Big Datasets

                          Goals for Tomorrow

                          • Resume Python Data-camp
                          • Resume Rock vs Mine Project
                          • Finish the first week of Andrew Ng


                          February 19, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Andrew Ng 1.7 hrs
                          • Cost Function
                          • Squared Error Cost Function
                          • Const Function Intuition

                          Goals for Tomorrow

                          • Use less time lying around
                          • Starting Khanacademy because I am falling behind
                          • Do more data-camp


                          February 18, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Machine Learning Project 5.8 hrs
                          • Line that is supposed to go through the points doesn’t seem right

                          Goals for Tomorrow

                          • Beautify the project with details about Linear Regression theory
                          • Spend less time on a project
                          • Use time efficiently
                          • Starting Khanacademy


                          February 17, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Python Data-camp 1.4 hrs
                          Andrew Ng 2.3 hrs
                          • Linear regression model training and estimated target

                          Goals for Tomorrow

                          • Understanding Model representation lab, eventually disscuss it with Safaet
                          • Start linear algebra from Kahanacademy
                          • Start Panda package tutorial


                          February 16, 2023

                          Activity Time Spent Things Learned Problem Faced
                          Progress Sheet 2 hrs
                          • Add to do list
                          • How to add same formula to the whole column
                          Git 2.1 hrs
                          • Reminiscing Git
                          • How to work in an existing git repository
                          • What happens if I change the location of a folder
                          Andrew Ng 1 hrs
                          • Linear regression
                          • Clustering Algorithm
                          • Anomaly Detection
                          • Dimentionality Detection
                          • Notations

                          Goals for Tomorrow

                          • Waste less time on the phone
                          • Recapture the git a little more
                          • Implement linear regression in Jupyter Notebook


                          Overall Learned

                          Programming

                          • Python
                            • Introduction to Python
                            • NumPy
                            • Matplotlib
                            • Pandas
                          • Markdown

                          Algorithm

                          • Supervised Machine Learing
                            • Regression
                              • Linear Regression
                                • For Single Variable (Univariate)
                                • Multiple Features
                            • Classification
                              • Logistic Regression
                          • Unsupervised Machine Learning
                            • Clustering
                            • Anomaly Detection
                            • Dimentionality
                          • Gradient Descent

                          Projects

                          • Student Score Prediction using Linear Regression (Univariate)
                          • Rock vs Mine Prediction using Logistic Regression

                          Deployment of Machine Learning Model

                          Visit original content creator repository https://github.com/wsamio/Progress-Sheet

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