Roadmap for Data Science
Data Science
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- 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
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INTERVIEW QUESTIONS
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Advance Excel by Anoop Yadav- VBA and Macros
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Capstone Project
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RESUME SESSION BY PALASH
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DATA SCIENCE PPT Notes
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