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Live Class Notes and Videos | Data Science
Machine Learning - 21.05.2021
21.05.2021- Machine Learning | Supervised & Unsupervised Learning Algorithm
22.05.2021- Numpy
23.05.2021- Pandas
24.05.2021- Linear Regression 1
25.05.2021-Linear Regression- Boston Housing Pricing Model
25.05.2021-Boston Dataset
26.05.2021- Boston Housing Pricing Model 2
27.05.2021- Dataset-Diabetes
27.05.2021- Matplotlib-1
28.05.2021- Matplotlib-2
28.05.2021-Data Preprocessing-1
29.05.2021- Data Preprocessing-2
29.05.2021-Boston Housing Feature Selection
31.05.2021-Logistic Regression
31.05.2021-Diabetic Classifier using Logistic Regression
31.05.2021- Concept of Classification.._
31.05.2021-Titanic Code file
01.06.2021-Data Preprocessing-3
01.06.2021-Diabetic Classifier using Logistic Regression
01.06.2021 Concept of Classification.._
01.06.2021-Titanic Logistic Regression
02.06.2021-Analysis Diabetic Classifier
02.06.2021-Flower Species Classification using KNN.ipynb - Colaboratory
02.06.2021-KNN.pptx
04.06.2021-Support Vector Machine (SVM)
04.06.2021- Assignment
05.06.2021-Project : MNIST Dataset
05.06.2021-Project: Digital Classification using Support Vector Machine
11.06.2021-Unsupervised Machine Learning-K Mean Clustering
11.06.2021-Customer Segmentation
11.06.2021- Code file- Mall_Customers
13.06.2021-Time Series Analysis
13.06.2021-Final Decision Tree Classifier.pptx
15.06.2021-Naive Bayes Classifier
15.06.2021-Naive Bayes and PCA
15.06.2021- PCA on iris.ipynb - Colaboratory
15.06.2021-Env command
23.05.2021-ALL CSV Data Frames
Code File
Python- Batch Start 07.06.2021
07.06.2021- Introduction, Variables, Constants, Litrals
08.06.2021- If-Else | Python Operators | Python Literals
10.06.2021- Loop (For, While, Break, Continue)
16.06.2021- Function 1
16.06.2021- Function 2
17.06.2021- Python String
17.06.2021- Python List
18.06.2021- Python Tuples
18.06.2021- Python Dictionary
21.06.2021- Numpy
22.06.2021- Pandas
23.06.2021- Matplotlib (61:22)
24.06.2021-Seaborn (61:49)
Artificial Intelligence- 25.06.2021
25.06.2021- Deep Learning | ANN (103:36)
26.06.2021- Doubt Clearing session (19:37)
29.06.2021- Artificial Neural Network (107:59)
30.06.2021- Diabetic Classifier using ANN (79:44)
01.07.2021-Diabetic Classifier using ANN (32:10)
02.07.2021- Convolution Neural Network (104:22)
05.07.2021-CNN Database
06.07.2021- Image classification using CNN Part -1 (83:22)
06.07.2021-ANN Home work
06.07.2021- Tomato Diseases Dataset
07.07.2021- Image classification using CNN Part -2 (77:38)
08.07.2021- Natural Language Processing (NLP) (57:27)
09.07.2021-NLP using Python ( Spacy, NLTK) (75:14)
10.07.20201- Text Classification using Python (74:12)
09.07.2021-Python
09.07.2021-Environment Setup Python Variable
15.07.2021-Python Operator Python Decision (72:03)
16.07.2021-Identifier, Operator (79:32)
17.07.2021- Decision Making and Loops In Python (74:04)
18.07.2021-Python Function (67:56)
19.07.2021-String and List (77:44)
20.07.2021-Python List | Tuple (89:32)
21.07.2021-Dictionary and Numpy (81:26)
22.07.2021-Data Sets
22.07.2021- Numpy 2 (60:38)
23.07.2021-Pandas (63:44)
27.07.2021- Python full notes
27.07.2021-Bengaluru_House_Data Set
27.07.2021-Pandas
27.07.2021- Video (111:57)
28.07.2021- Matplotlib | Seaborn | Numpy
Tableau-15.07.2021
Dataset-15.07.2021
15.07.2021- Tableau Introduction, Different types of visualization using Tableau (78:24)
16.07.2021- Different kind of visualization using tableau (82:42)
17.07.2021-Filter , Dashboard, Storytelling (76:24)
19.07.2021-Data join , Data Blend , Story Telling (82:48)
20.07.2021-Forecasting and cluster in python (52:53)
20.07.2021-Covid Data set archive
21.07.2021-Attrition Analysis (43:50)
21.07.2021- Notes
Business Analytics | Data Analytics - 22.07.2021
22.07.2021-Data Analytics across Domains | What is Analytics | Types of Analytics | AI vs ML vs DL vs DS (64:03)
29.07.2021-Hypothesis Testing , Analysis Of Variance And Covariance And Probability Distribution | A.I Vs ML Vs DL Vs DS (118:21)
29.07.2021-Dataset
30.07.2021-Statistical Testing, Probability Theory For Data Analytics And Type Of Probability Distribution (84:15)
31.07.2021-Data Science with Python (79:50)
02.07.2021-Data Science With Python, Data Science Application across Multiple Domain (114:32)
03.08.2021-Data Science Project LifeCycle Multiple Predictive Model using Python (110:35)
04.08.2021-ython - Simple and Multiple Predictive Model in Practical Python Correlation Analysis (125:38)
06.08.2021-Python Classification Model Building (118:59)
06.08.2021-Data Science - Experimental Design Analysis (120:47)
06.08.2021- Assignment
07.08.2021-Python Classification Modeling .. (Customer Churn Predective Modeling) (119:45)
10.08.2021-Python Classification Modeling .. (Customer Churn Predective Modeling)-Part 2 (66:07)
11.08.2021-Churn prediction classification for telecommunication company (python classification model building) (114:38)
12.08.2021-Data Science- Association rule - Apriori Algorithm (83:04)
13.08.2021- Image Processing and Image Extraction Image Processing and Object Recognition (144:59)
14.08.2021-Data Science - Building Recommendation System - (Market Basket Analysis) (112:38)
Python: 16.08.2021
16.08.2021-Environment Setup Python Variable (125:58)
17.08.2021-Python Operator and Python Decision (117:30)
18.08.2021-Control Statement Python Function & Module (113:12)
19.08.2021-Python Strings , Python List (119:37)
20.08.2021-Operator in Python (118:18)
23.08.2021-Python Module and Pandas (117:41)
24.08.2021-Pandas Library in Python (113:11)
25.08.2021- Matplotlib and Pandas (118:25)
26.08.2021- matplotlib (111:13)
28.08.2021-Numpy (123:27)
30.08.2021- Exception Handeling, Iterator and Generator (142:49)
31.08.2021- Exception Handeling- Part 2 (118:51)
Machine Learning- 01.09.2021
01.09.2021- Machine Learning Introduction, Overview of Supervised, Unsupervised Learning Algorithm (119:34)
02.09.2021-Classification and Regression Technique (122:00)
03.09.2021-Linear Regression (131:13)
04.05.2021- Doubt Clearing Session (86:27)
06.09.2021-Logistics Regression (116:45)
07.09.2021- Sigmoid Function and Logic Function (121:41)
08.09.2021 Correlation Analysis (72:22)
Machine Learning By Barun Kr. Mishra- 09.09.2021
09.09.2021- Machine Learning Introduction, Overview of Supervised, Unsupervised Learning Algorithm (99:05)
10.09.2021- Numpy (82:49)
11.09.2021- Pandas (126:04)
13.09.2021- Matplotlib (133:17)
14.09.2021 - Co-Relation Analysis (101:40)
15.09.2021 - Simple Linear Regression & Multiple Linear Regression (113:21)
16.09.2021 - Logistic Regression Concepts & Odds Ratio (133:09)
17.09.2021 Logit Function & Sigmoid Function Cost function for logistic regression (102:22)
20.09.2021 Evaluation Matrix and Confusion Matrix & Odd’s Ratio and ROC Curve (109:21)
21.09.2021 Discriminant Analysis & Statistics Associated with Discriminant Analysis (126:26)
22.09.2021 Naïve Bayes Concepts & Python Execution of Naïve Bayes (143:33)
23.09.2021 Distance as Classier, Euclidean Distance, Manhattan Distance, KNN Basics,KNN for Regression & Classification (133:13)
24.09.2021 Basics of SVM, Margin Maximization, Kernel Trick, RBF Poly Linear (109:52)
27.09.2021 Decision Tree Concrpts, Coding (125:06)
28.09.2021 Random Forest Concepts & Coding (115:46)
29.09.2021 Clustering (108:29)
30.09.2021 KMeans (102:12)
01.10.2021 Time Series, Arima and Sarima, Trends & Seasonality (118:37)
02.10.2021 Doubt Session (77:54)
04.10.2021 Project (103:44)
05.10.2021 Project (91:26)
06.10.2021 Project (117:21)
07.10.2021 Project (63:31)
08.10.2021 Installation Set-Up (112:02)
09.10.2021 Doubt Session (55:22)
11.10.2021 Introduction to R Basics (111:22)
12.10.2021 R Matrices (107:25)
16.10.2021 R Data Frames (95:59)
18.10.2021 R Lists (107:20)
19.10.2021 Data Input & Output R (104:38)
20.10.2021 R Programming Basics (100:10)
21.10.2021 Advanced R Programming (115:28)
22.10.2021 Data Manipulation with R (107:00)
26.10.2021 Linear Regression R (121:05)
27.10.2021 K Nearest Neighbors (110:16)
28.10.2021 K Nearest Neighbors (106:21)
29.10.2021 Random Forest (106:42)
30.10.2021 Support Vector Machine (98:09)
01.11.2021 Decision Tree and Random Forests Question (106:47)
02.11.2021 Doubt Session of R Topics (72:53)
Python 8th Nov'2021
08.11.2021 Environment Setup Python Variable (103:40)
10.11.2021 Data Types in Python (99:37)
11.11.2021 Python Strings & SETS (95:14)
12.11.2021 Tuples and Dictionaries (96:52)
13.11.2021 Doubt Session (106:12)
15.11.2021 Numpy (110:15)
16.11.2021 Pandas (114:29)
17.11.2021 Pandas (108:54)
18.11.2021 Matplotlib (115:41)
19.11.2021 Matplotlib + Seaborn (110:35)
20.11.2021 Matplotlib & Doubt (103:20)
22.11.2021 Matplotlib (105:41)
Tableau 23.11.2021
23.11.2021 Tableau Introduction & Different Types of Visualization Using Tableau (121:23)
24.11.2021 Formatting in Tableau and the 1st Bar chart (108:23)
25.11.2021 Working with Data Extract in Tableau (99:34)
26.11.2021 Aggregation & Granularity (100:25)
27.11.2021 Interview Session Related to Python (109:33)
29.11.2021 Joining Data in Tableau (101:50)
30.11.2021 Scatter Plot, Filtering, Working on Multiple Sheets (101:44)
01.12.2021 Joining and Blending (114:47)
02.12.2021 Table Calculations (108:36)
03.12.2021 Parameters, Dashboard Creation, Advanced Dashboard (107:49)
04.12.2021 Doubt Session (117:35)
06.12.2021 Retail Sector Forecast (102:03)
07.12.2021 Project on Tableau Discussion (102:32)
08.12.2021 Time Series Blending (103:16)
09.12.2021 Background Maps & Images in Tableau (84:55)
10.12.2021 Level of Detail Calculations Profit Analysis (104:52)
11.12.2021 Seminar on Future of Data Science and AI (102:55)
13.12.2021 Dashboard with Different Sectors (97:46)
14.12.2021 Revision of Tableau (94:55)
Business Analytics 15th Dec'2021
15.12.2021 What is Analytics , Types AI vs ML vs SL vs DS (99:05)
16.12.2021 Descriptive & Inferential Statistics (102:19)
17.12.2021 Measurement of Scales (110:41)
18.12.2021 Doubts Session (96:13)
20.12.2021 Parametric & Non Parametric Tests (99:22)
21.12.2021 Hypothesis Testing & Inferential Statistics (108:51)
22.12.2021 Statistical Tests with Examples (99:00)
23.12.2021 ANOVA & ANCOVA (99:43)
24.12.2021 Probability & Probability Distribution (105:25)
27.12.2021 Tests (57:21)
28.12.2021 Questionnaire Design (118:09)
29.12.2021 Data Science with Python & it-s Application (96:58)
30.12.2021 Predictive Model Using Python (105:18)
31.12.2021 Correlation Analysis Using Python (87:42)
03.01.2022 Simple and Multiple Predictive Model (114:12)
04.01.2022 EDA (115:17)
05.01.2022 Experimental Analysis (113:56)
06.01.2022 Discriminant Analysis (105:41)
07.01.2022 Association Rule (105:14)
08.01.2022 Doubt Session (81:21)
10.01.2022 Market Basket Analysis (104:47)
11.01.2022 Image Processing (102:08)
Live Class Machine Learning & Artificial Intelligence Jan-2022
12.01.2022 Machine Learning Introduction ,Overview of Supervised, Unsupervised Learning Algorithm (97:41)
13.01.2022 Simple Linear Regression & Multiple Linear Regression (97:32)
14.01.2022 Logistic Regression Concepts & Odds Ratio (106:17)
15.01.2022 Doubts Clearing Session (102:54)
17.01.2022 Evaluation Matrix Confusion Matrix, Odd’s Ratio & ROC Curve (100:35)
18.01.2022 Confusion Matrix, Odds Ratio, OC Curve (102:54)
19.01.2022 Sigmoid Function & Cost Function (103:47)
20.01.2022 Discriminant Analysis (103:36)
21.01.2022 Naive Bayes Theorem (107:30)
22.01.2022 Discussion on Interview Questions and Doubt Clearance (88:43)
24.01.2021 SVM (99:42)
25.01.2022 KNN (107:54)
27.01.2022 Trends, Seasonality (106:30)
28.01.2022 Time Series (101:37)
29.01.2022 Arima & Sarima (108:04)
31.01.2022 Business Analytics Project (110:04)
Live Class Python Feb'2022
01.02.2022 Environment Setup Python Variable (110:50)
02.02.2022 Python Operator Python Decision (106:49)
03.02.2022 Control Statement Python Function & Module (111:07)
04.02.2022 Data Types-List and Tuples (107:47)
05.02.2022 Doubt Session (102:30)
07.02.2022 Data Types- Dictionary and Set (104:03)
08.02.2022 Numpy (110:50)
09.02.2022 Pandas Library (102:44)
10.02.2022 Pandas Library (110:21)
11.02.2022 Matplotlib Library (116:10)
12.02.2022 Matplotlib and Doubt Session (106:31)
14.02.2022 Matplotlib and Seaborn (105:02)
15.02.2022 Matplotlib continue and seaborn library (67:38)
Live Class Data Analytics Feb & Mar'2022
16.02.2022 What is Business Analytics Tools used for it (124:30)
17.02.2022 Descriptive Statistics (128:29)
18.02.2022 Inferential Statistics (114:39)
19.02.2022 Doubt Session (101:39)
21.02.2022 Types of Statistical Tests (107:57)
22.02.2022 Non Parametric Tests practical (110:53)
24.02.2022 Parametric tests Practical (106:04)
26..02.2022 Probability Distribution (66:08)
26.02.2022 Doubt Session (32:37)
28.02.2022 Correlation (96:28)
01.03.2022 Linear Regression Analysis (56:11)
03.03.2022 Linear Regression (57:23)
04.03.2022 Multiple Regression (59:42)
05.03.2022 Doubt Session (50:28)
07.03.2022 ANOVA (59:51)
08.03.2022 Experimental Design (49:49)
09.03.2022 Discriminant Analysis (10:35)
10.03.2022 Factor Analysis (56:52)
12.03.2022 Association Rules (59:13)
Live Class SQL Mar'2022
14.03.2022 SQL Introduction (64:20)
15.03.2022 DDL Commands (62:23)
16.03.2022 DML Commands (1311:18)
21.03.2022 DCL Commands (66:52)
22.03.2022 Creating user, Assigning rights, Types of User and Tables in it (56:49)
23.03.2022 SQL Joins (53:27)
24.03.2022 Views and Procedure in SQL (56:43)
25.03.2022 Procedures and Function (49:08)
26.03.2022 Workshop on Data Science (65:14)
28.03.2022 Triggered in SQL (59:08)
29.03.2022 SQL Doubts and Test (69:53)
Live Class Machine Learning Mar & April '2022
30.03.2022 Machine Learning Introduction. Supervised and Unsupervised Learning (98:53)
31.03.2022 Correlation Analysis (122:37)
01.04.2022 Linear Regression (113:34)
02.04.2022 Introduction to Logistic Regression (119:55)
04.04.2022 Discriminant Analysis (113:36)
05.04.2022 Cluster Analysis (107:19)
06.04.2022 Naive Bayes Theorem (78:09)
07.04.2022 ANOVA (117:10)
08.04.2022 KNN Algorithm (111:33)
09.04.2022 Doubt Session (86:22)
11.04.2022 Support Vector Machine (110:00)
12.04.2022 Decision Tree (105:21)
13.04.2022 Decision Tree and Random Forest (100:10)
14.04.2022 Factor Analysis (111:52)
15.04.2022 ROC Curve, Cost and Sigmoid Function (105:59)
16.04.2022 Doubt Session (74:39)
18.04.2022 Agglomerative Clustering (101:48)
19.04.2022 Assignments (99:54)
Live Class Artificial Intelligence April '2022
21.04.2022 What is AI (84:34)
22.04.2022 Deep Learning (108:14)
23.04.2022 Doubt Session (102:10)
25.04.2022 Convolutional Neural Network (103:46)
26.04.2022 CNN Practical Aspect (112:18)
27.04.2022 Recurrent Neural Network (93:34)
28.04.2022 RNN Practical (109:19)
29.04.2022 Artificial Neural Network (97:02)
30.04.2022 Doubt Session (106:57)
02.05.2022 Boltzmamn Machine (107:14)
04.05.2022 Boltzmann machine hands-on (114:37)
Live Class Power BI May' 2022
05.05.2022 Introduction to Power BI (109:12)
06.05.2022 Types of charts and their usage (111:22)
09.05.2022 Plotting different charts, Formatting (104:57)
10.05.2022 Ribbons,Cards, maps (115:20)
11.05.2022 Maps, scatterplot, Gauge Charts (121:18)
12.05.2022 Aggregation and Granularity (114:15)
13.05.2022 Time Series Data and Drill Down and Drill Up (113:16)
14.05.2022 Doubt Session (93:43)
16.05.2022 Power Query (116:04)
17.05.2022 Import Data from from different sources (108:24)
18.05.2022 DAX Formulas (110:42)
19.05.2022 DAX Formulas (107:39)
20.05.2022 Date Functions and Calculate Functions (111:45)
Live Class Python May' 2022
23.05.2022 Introduction (109:54)
24.05.2022 Data Types in Python (106:39)
25.05.2022 Data Types Continue (114:32)
26.05.2022 Sets and Strings (107:38)
27.05.2022 Details of Numpy Library (64:01)
30.05.2022 Pandas library (113:12)
31.05.2022 Pandas Continue (107:49)
01.06.2022 Matplotlib Library (171:47)
02.06.2022 Matplotlib and Seaborn (110:58)
03.06.2022 Seaborn Library (60:14)
04.06.2022 Doubt Session (86:19)
06.06.2022 Doubts and Questions of Python (89:09)
Business Analytics June' 2022
07.06.2022 Introduction (101:41)
08.06.2022 Descriptive and Inferential Statistics (109:13)
09.06.2022 Hypothesis Testing (113:43)
10.06.2022 Probability Theory and Distribution (64:29)
13.06.2022 Probability Theory and Distribution (104:38)
14.06.2022 One Way ANOVA and Probability Distribution (101:35)
15.06.2022 Two Way ANOVA (121:15)
16.06.2022 Statistical Tests Non Parametric (105:21)
17.06.2022 Non Parametric Tests (106:28)
18.06.2022 Doubt Session (28:00)
20.06.2022 Parametric Tests (104:45)
21.06.2022 Correlation Analysis (98:28)
22.06.2022 Simple and Multiple Modelling (89:01)
23.06.2022 Discriminant Analysis (115:10)
24.06.2022 Experimental Design Analysis (107:35)
25.06.2022 Doubt Session (50:25)
27.06.2022 Market Basket Analysis (118:18)
28.06.2022 Image Processing and Object Recognition (92:02)
29.06.2022 Measuring scales and Questionaires (113:24)
02.07.2022 Test (30:23)
Tableau July' 2022
30.06.2022 Introduction (89:59)
02.07.2022 Doubt Session (30:23)
04.07.2022 Types of Charts in Tableau (99:16)
05.07.2022 Visualisation with Maps (92:39)
06.07.2022 Working with Time Series (94:19)
09.07.2022 Doubt Session (82:20)
11.07.2022 Multiple join in Tableau (91:59)
12.07.2022 Working on Multiple Sheets and Formatting (104:13)
14.07.2022 Tabulation and Histogram (109:15)
15.07.2022 Tree Map, Parameters, Dashboard (102:42)
16.07.2022 Dashboard creation (40:20)
18.07.2022 Story Telling in Tableau (68:07)
19.07.2022 Tableau case study discussion (93:54)
20.07.2022 Doubt Clearing Session (77:52)
Data Analytics July' 2022
21.07.2022 Introduction (86:54)
22.07.2022 Correlation Analysis (107:40)
23.07.2022 Doubt Session (62:46)
25.07.2022 Regression Analysis (95:55)
27.07.2022 Multiple Regression (105:07)
29.07.2022 Logistics Regression (110:00)
05.08.2022 Discriminant Analysis (102:58)
06.08.2022 Factor Analysis (93:49)
12.08.2022 Characteristics of Naive Bayes (116:00)
13.08.2022 Support Vector Machine (106:39)
19.08.2022 Naive Bayes Theorem (104:04)
20.08.2022 Project on Linear, Multiple, Logistics Regression (116:32)
27.08.2022 Decision Tree (101:15)
28.08.2022 Decision Tree (73:37)
02.09.2022 Random Forest (86:27)
03.09.2022 Decision Tree (75:04)
09.09.2022 Interview session (89:03)
10.09.2022 Doubt Session (85:58)
Python Sep' 2022
17.09.2022 Introduction (92:37)
23.09.2022 Data Types in Python (114:13)
24.09.2022 Numpy Library (96:10)
30.09.2022 Matplotlib Library (74:50)
01.10.2022 Matplotlib Library (88:24)
Python June' 2023
Session-1 Introduction to Python (108:55)
Session-2 Variables In Python (100:07)
Session-3 Operators in Python and Data Types (91:34)
Session-4 Dictionary and Set Concept In Python (22:01)
Session-5 Conditional Statements and Loop in Python (93:24)
Session-6 Loop In Python (98:08)
Session-7 String In Python (107:17)
Session-8 Methods Of String (70:14)
Session-9 Function In Python (93:06)
Session-10 File Handling (37:59)
Session-11 Methods Of File Handling (104:08)
Session-12 Exception Handling (105:10)
Session-13 Concept Of Module In Python (98:15)
Session-14 Libraries In Python (94:06)
Session-15 Pandas Library In Python (102:24)
Session-16 Pandas Merge (97:16)
Session-17 Numpy (91:23)
Session-18 Numpy Functions (97:41)
Session-19 Matplotlib (96:09)
Session-20 Seaborn Functionality (72:32)
Machine Learning Oct' 2023
Session-1 Introduction (53:31)
Session-2 Supervised Learning In ML (93:13)
Session-3 Logistics Regression Algorithm (98:53)
Session-4 Feature Engineering (83:41)
Session-5 Feature Engineering (53:53)
Session-6 Feature of Transformation (127:44)
Session-7 Outlier Detection (68:55)
Session-8 Outlier Detection (84:35)
Session-9 Statistics For Machine Learning (84:44)
Session-10 Statistics For Machine Learning (84:44)
Session-11 Statistics For Machine Learning (84:44)
Session-12 Machine Learning Project (80:41)
Session-13 Natural Language Processing (31:14)
Session-14 Stemming and lemmatization in NLP (81:08)
Session-15 Lemmatization in NLP (99:06)
Session-16 MySQL (80:08)
Python Nov' 2023
Session-1 Basic of Python (92:28)
Session-2 Concept of Variable In Python (84:35)
Session-3 While Loop (74:31)
Session-4 String Concept (78:06)
Session-5 Methods Of String (82:40)
Session-6 Concept Of Function (80:17)
Session-7 Lambda Function (85:59)
Session-8 File Handling and Exception Handling (68:21)
Session-9 Modules In Python (81:30)
Session-10 Exception Handling (85:50)
Session-11 Regular Expression (54:52)
Session-12 Finally Block In Exception Handling (68:54)
02.04.2022 Introduction to Logistic Regression
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