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Optimal Control by Prof. G.D. Ray,Department of Electrical Engineering,IIT Kharagpur.For more details on NPTEL visit ...

Lecture 22 : Tutorial Session - 4: Python implementation of Jacobi Method.

This video is part of the Mooc “Machine learning in Python with scikit-learn ” hosted on FUN platform: ...

Parameter Estimation, Slope , Intercept, ANOVA, Residual, R-square.

In this video we are going to take a look at logistic regression. Unlike linear regression, analysis of variance (ANOVA), and ...

Mamba is a new neural network architecture that came out this year, and it performs better than transformers at language ...

Lecture 13 : Tutorial Session - 2: Python Coding for Naive Gaussian Elimination Method.

Course website: http://bit.ly/DLSP20-web Playlist: http://bit.ly/pDL-YouTube Speaker: Alfredo Canziani Week 1: ...

All lesson resources are available at http://course.fast.ai.) In this lesson, we dive into backpropagation and the creation of a simple ...

Week 4: Tutorial 04 Part 01: Plotting In 1 D Using Python.

Lecture 1 : Introduction.

Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the "sexiest job of the 21st ...

Lecture 15: Regression.

Professor Patrick Sturgis, NCRM director, in the first (of three) part of the Structural Equiation Modeling NCRM online course.

00:00:00 - Introduction 00:01:59 - Linear model and neural net from scratch 00:07:30 - Cleaning the data 00:26:46 - Setting up a ...

Session 04: Mastering Searching Algorithms | Linear Search vs Binary Search Welcome to the 4th session of our 25-part series!

Week 07: Lecture 34: Demand Forecasting using AI/ML: Building Regression Tree Model using Python.

00:00 Introduction and survey 01:36 "Lesson 0" How to fast.ai 02:25 How to do a fastai lesson 04:28 How to not self-study 05:28 ...

Heteroscedastic Residual, Multiple Linear Regression, ANOVA, K-fold cross-validation, Model adequacy.

10 cases help you to solving linear equations by computer program how to do the interpolation but that is somehow against ...