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Complete Data Science Course - CX 75
Data Science
DATA SET FILE
Session-1(08-07-2023) OOPs (132:59)
Session-2(09-08-2023)Python Basics (122:17)
Session-3(15-07-2023) Maths with Python (129:57)
Session-4(22-07-2023) Population and Sample (127:50)
Session-5(23-07-2023) Kurtosis and Stats (95:18)
Session-6(29-07-2023) Derivative and Continuity of Maths (123:12)
Session-7(30-07-2023) Varoius types of Analysis (68:08)
Session-8(05-08-2023) ML Algorithms (126:44)
Session-9(06-08-2023) Training and Testing and Samplings (122:51)
Session-10(12-08-2023)Data Discretization Techniques (97:27)
Session-11(13-08-2023) Imputation Techniques and Random Forest (69:09)
Session-12(19-08-2023)Naive Bayes Algo (110:46)
Session-13(26-08-2023)Linear and Logistic Regression (134:03)
Session-14( 27-08-2023) Advanced Linear Regression Techniques (104:18)
Session-15(02-09-2023) Decesion tree and Entropy (101:48)
Session-16(03-09-2023) Bias and Variance Trade-off (93:51)
Session-17(09-09-2023) Stacking Models, Cascade Models, Feature Engineering, NLP Basics (79:13)
Session-18(10-09-2023) Text Pre-processing, Personalised Cancer Diagnosis (121:37)
Session-20(17-09-2023) Amazon Fine Food Review Analysis (Applications of Clustering) (121:14)
Session-21(24-03-2023) Neural Networks (78:00)
Session-22(30-09-2023) Backpropagation Algorithm (86:44)
Session-23(1-10-2023)Practical Execution of Backpropagation (95:20)
Project for DS
ML
INTERVIEW QUESTIONS
INTERVIEW QUESTIONS
Advance Excel by Anoop Yadav- VBA and Macros
Session-1 (11-11-2023) (158:50)
Session-2(12-11-2023) (130:49)
Session-3(16-11-2023) (110:38)
Session-4(20-11-2023) (78:25)
Capstone Project
Fraud Transaction Detection
Heart Disease Prediction
RESUME SESSION BY PALASH
Resume Session (134:40)
DATA SCIENCE PPT Notes
ML Supervised
ML Unsupervised
Statistics and Probability
Introduction to Machine Learning
Deep Learning and NLP
Session-16(03-09-2023) Bias and Variance Trade-off
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