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Yash Choudhari

Python | SQL | Machine Learning

Skills Acquired at Skill-Lync :

  • PYTHON
  • DATA SCIENCE

Introduction

Currently pursuing the course in data science and data analyst. Interest in analyzing the data and digging out the insights of the data. Known programming languages of mine are Python, SQL. Hard Skills : 'Pandas', 'Numpy', 'MYSQL', 'Machine Learning technology' ,'SKlearn' , 'Exploratory Data Analysis.

26 Projects

Project 1 English Dictionary App

Objective:

The file for project 1 has been attached below. Thank You

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21 Oct 2021 02:53 PM IST

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    Project 2 Library Book Management System

    Objective:

    The file for project 2 has been attached below Thank You.

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    07 Nov 2021 08:58 AM IST

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      Basics of Probability and Statistics Week 1 Challenge

      Objective:

      1. Why there is a difference in the formula of variance for population and sample Formula of variance for population =∑(Xi−u)2/n Formula of variance for sample =∑(Xi−u)2/n-1 Because variance for population is calculated from the population data,and the variance for sample is calculated from sample data…

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      09 Nov 2021 03:19 PM IST

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        Basics of ML & AL Week 2 Challenge

        Objective:

        1.Calculate all 4 business moments using pen and paper for the below data set? For the 1 question images has been attached below 2.What is the significance of expected value when simple mean (Sum of all observations/number of observations) is already in place The mean is calculated for the uniform probability distribution…

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        13 Nov 2021 04:23 AM IST

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          Supervised Learning - Prediction Week 3 Challenge

          Objective:

          1.Perform Gradient Descent in Python with any loss function m=0 b=0 l=0.001 epochs=1000 n = float(len(x)) for i in range(len(x)): y_pred = m*x + b d1 = (-2/n) * sum(x * (y-y_pred)) d2 = (-2/n) * sum(y-y_pred) m = m-l*d1 b = b-l*d2 print(m,b) 2.Difference between L1 & L2 Gradient descent method L1 = mean absolute error…

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          15 Nov 2021 04:49 PM IST

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            Supervised Learning - Classification Week 7 Challenge

            Objective:

            1.Pros and cons of SVMAdvantages:SVM works relatively well when there is a clear margin of separation between classes.SVM is more effective in high dimensional spaces.SVM is effective in cases where the number of dimensions is greater than the number of samples.SVM is relatively memory efficientDisadvantages:SVM algorithm…

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            01 Dec 2021 05:48 AM IST

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              Supervised Learning - Classification Week 8 Challenge

              Objective:

              1.Apply knn to the “Surface defects in stainless steel plates” and identify the differencesAccuracy for SVM with train test = 70% : 30% is 73%.Accuracy for KNN with train test = 70% : 30% is 72%.So here in KNN we are losing our accuracy by 1% compare to SVM.The file for 1 question has been attached below 2.What…

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              01 Dec 2021 09:44 AM IST

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                Unsupervised Learning - Kmeans Week 11 Challenge

                Objective:

                1.How does similarity is calculated if data is categorical in natureThe similarity between categorical data is calculated as 0 and 1.if two data are same then it is 0 and if they are different it is 1. 2.Implement K-means for “Car dataset” and come up with the business insightsFile for this question has been…

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                03 Dec 2021 10:42 AM IST

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                  Supervised Learning - Classification Week 9 Challenge

                  Objective:

                  1.What is a Neural Network?Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling or clustering raw input. 2.What is deep learning?Deep Learning is a subfield of machine learning…

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                  08 Dec 2021 05:20 AM IST

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                    Project 1

                    Objective:

                    The file for Project 1 has been attached below Thank You

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                    09 Dec 2021 10:51 AM IST

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                      Project 2

                      Objective:

                      The file for Project 2 has been attached below Thank You.

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                      12 Dec 2021 05:54 AM IST

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                        Project 1

                        Objective:

                        As i couldn't find the data here so i have created my own data and performed the logistic regression using Simple and Stratified sampling. File has been attached for this question.

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                        10 Jan 2022 07:26 AM IST

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                          Project 2

                          Objective:

                          Final Project : To perform gradient descent for more than one input features and on pen and paper also for 2 iteration. images and file has been attached.

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                          11 Jan 2022 05:16 AM IST

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                            Project 1

                            Objective:

                            File has been attached for Project 1

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                            03 Feb 2022 05:02 AM IST

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                              Project 2

                              Objective:

                              For Question No for 4 Python file has been attached For Question No 5 and 13 Excel file has been attached For all other questions SQL file has been attached

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                              15 Feb 2022 06:11 AM IST

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                                Project 1

                                Objective:

                                File has been attached

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                                21 Feb 2022 04:43 AM IST

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                                  Project 2

                                  Objective:

                                  Q.Write steps for gradient descent for 2 input features and output having 3 classes. 1.Loss function = -[ yloga1 + y2loga2 + y3loga3 + y4loga4] 2.We have to found derivatives for 0th layer with respect to z 3.We have to found derivatives for 1st hidden layer by applying any activation function 4.As we know we have 3 classes…

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                                  21 Feb 2022 04:57 AM IST

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                                    Project 4

                                    Objective:

                                    I didn't find any dataset here and i want to try that what happens to regularization with single input feature so i used my own dataset. File has been attached below.

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                                    03 Mar 2022 07:07 AM IST

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                                      Project 5

                                      Objective:

                                      Q.Identify the working principle of all 5 GBM and list down its advantages and disadvantages? AdaBoostAdaBoost also called Adaptive Boosting is a technique in Machine Learning used as an Ensemble Method. The most common algorithm used with AdaBoost is decision trees with one level that means with Decision trees with only…

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                                      03 Mar 2022 07:10 AM IST

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                                        Project 7

                                        Objective:

                                        Q.1 Where do we use 2 level of padding?We use 2 level of padding when we want our output to have 1 level of padding (i.e an frame on an output image). Q.2 What is the formula to evaluate the dimension of output in terms of padding and stride?Formula = n + 2p - f + 1 / swhere n = input dimensionp = paddingf = filter layers…

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                                        31 Mar 2022 05:53 AM IST

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                                          Project 9

                                          Objective:

                                          Q.1 Explain vanishing gradient problem in RNN The vanishing gradient problem occurs when the backpropagation algorithm moves back through all of the neurons of the neural net to update their weights. The nature of recurrent neural networks means that the cost function computed at a deep layer of the neural net will be…

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                                          01 Apr 2022 02:29 PM IST

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                                            Project 8

                                            Objective:

                                            As mentioned in the lecture to find a dataset from opensource i have found my own dataset and i worked on that. The file has been attached below. Thank You.

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                                            02 Apr 2022 08:30 AM IST

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                                              Project 10

                                              Objective:

                                              I have applied LSTM and the file has been attached below. Thank You.

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                                              04 Apr 2022 03:15 PM IST

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                                                Project 3

                                                Objective:

                                                The file has been attached below.

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                                                15 Apr 2022 10:29 AM IST

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                                                  Project 6

                                                  Objective:

                                                  The file has been attached below.

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                                                  15 Apr 2022 10:30 AM IST

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                                                    Project 11

                                                    Objective:

                                                    The file has been attached below.

                                                    calendar

                                                    15 Apr 2022 10:31 AM IST

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                                                      Showing 1 of 26 projects

                                                      5 Course Certificates

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                                                      Core and Advanced Python Programming

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                                                      Machine Learning Fundamentals In Depth

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                                                      Math behind Machine Learning & Artificial Intelligence using Python

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                                                      SQL for Data Science

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                                                      Advanced Deep Learning using Python

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                                                      Academic Qualification

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                                                      SSR College of Arts, Science and Commerce

                                                      04 Jun 2018 - 13 Apr 2021

                                                      12th

                                                      P. G. Junior College

                                                      12 Jun 2017 - 16 Feb 2018

                                                      10th

                                                      P.C.G.ENG.MED.HIGH.SCHOOL

                                                      15 Jun 2015 - 25 Mar 2016

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