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| 001 Module-1.pptx |
1007.21Кб |
| 001 PPT.html |
872б |
| 002 Overview of Contents.mp4 |
3.22Мб |
| 003 The Bigger Picture.mp4 |
11.42Мб |
| 004 The Problem Landscape.mp4 |
21.53Мб |
| 005 Defining Data Science.mp4 |
12.22Мб |
| 006 Demystifying AI-ML-Data Science.mp4 |
7.76Мб |
| 007 Exploring the Data Scientists Toolbox.mp4 |
18.82Мб |
| 008 Download PPT and Code.html |
890б |
| 008 Module-2.pptx |
3.10Мб |
| 008 Module-2-Codes.zip |
4.52Кб |
| 009 Overview of Contents.mp4 |
3.24Мб |
| 010 Quick recap of Python.mp4 |
8.57Мб |
| 011 Python 2.7 vs Python 3.5.mp4 |
7.95Мб |
| 012 Installation Setup.mp4 |
20.41Мб |
| 013 Datatypes Overview.mp4 |
9.85Мб |
| 014 Spyder tour.mp4 |
5.94Мб |
| 015 Datatypes demo.mp4 |
41.72Мб |
| 016 Datatypes- Numpy.mp4 |
19.24Мб |
| 017 Datatypes-Pandas.mp4 |
18.34Мб |
| 018 Data Engineering.mp4 |
49.75Мб |
| 019 Data Engineering 2.mp4 |
12.91Мб |
| 020 Data Engineering 3.mp4 |
20.65Мб |
| 021 Functions.mp4 |
13.42Мб |
| 022 Data Visualization.mp4 |
60.69Мб |
| 023 Download PPT and Code.html |
890б |
| 023 Module-3.pptx |
3.15Мб |
| 023 Module-3-Codes.zip |
1.79Кб |
| 024 Overview of Contents.mp4 |
2.44Мб |
| 025 Machine Learning Methodology.mp4 |
13.61Мб |
| 026 Exploratory Data Analysis.mp4 |
6.03Мб |
| 027 Univariate Analysis.mp4 |
14.62Мб |
| 028 Univariate Analysis 2.mp4 |
30.74Мб |
| 029 Bivariate Analysis.mp4 |
55.23Мб |
| 030 Feature Engineering.mp4 |
34.74Мб |
| 031 Introduction to Statistics.mp4 |
30.44Мб |
| 032 Probability Distributions.mp4 |
14.54Мб |
| 033 Download PPT and Code.html |
890б |
| 033 Module-4.pptx |
4.08Мб |
| 033 Module-4-Codes.zip |
7.55Кб |
| 034 Overview of Contents.mp4 |
4.70Мб |
| 035 Introduction to Machine Learning.mp4 |
34.16Мб |
| 036 Supervised Learning.mp4 |
5.91Мб |
| 037 Simple Multiple Linear Regression.mp4 |
23.80Мб |
| 038 Regression Demo.mp4 |
30.98Мб |
| 039 Classification - Logistic Regression.mp4 |
17.69Мб |
| 040 Classification Logistic Regression Demo.mp4 |
19.99Мб |
| 041 Decision Trees.mp4 |
35.50Мб |
| 042 Decision Trees Demo.mp4 |
39.26Мб |
| 043 Unsupervised Learning - Clustering.mp4 |
18.19Мб |
| 044 Unsupervised Learning Clustering Demo.mp4 |
14.56Мб |
| 045 Unsupervised Learning -Association Rules.mp4 |
8.92Мб |
| 046 Model Evaluation - Regression.mp4 |
7.85Мб |
| 047 Model Evaluation - Regression Demo.mp4 |
19.48Мб |
| 048 Model Evaluation - Classification.mp4 |
14.72Мб |
| 049 Model Evaluation - Classification Demo.mp4 |
25.97Мб |
| 050 Regularization Hyperparameter tuning.mp4 |
21.05Мб |
| 051 Bias Variance Tradeoff.mp4 |
12.69Мб |
| 052 Cross Validation.mp4 |
10.97Мб |
| 053 Hyperparameter Tuning.mp4 |
10.23Мб |
| 054 Cross Validation Hyperparameter Demo.mp4 |
41.55Мб |
| 055 Ensemble Modeling.mp4 |
27.05Мб |
| 056 Random Forest Bagging.mp4 |
13.97Мб |
| 057 XGBoost Boosting.mp4 |
7.20Мб |
| 058 RF XGB Demo.mp4 |
30.20Мб |
| 059 Download PPT Code and Data.html |
902б |
| 059 Module-5.pptx |
2.90Мб |
| 059 Module-5-Code-Data.zip |
1006.26Кб |
| 060 Overview of Contents.mp4 |
6.12Мб |
| 061 Project Use Case Overview.mp4 |
15.68Мб |
| 062 Defining the Problem Statement.mp4 |
10.22Мб |
| 063 Business Solution Blueprint.mp4 |
22.15Мб |
| 064 Explore Define a ML use case.mp4 |
15.66Мб |
| 065 EDA and Feature Engineering.mp4 |
27.11Мб |
| 066 Approach for Model Development Evaluation Optimization.mp4 |
22.98Мб |
| 067 Storyboarding.mp4 |
10.78Мб |