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Rohan Raha
เข้าร่วมเมื่อ 15 ก.ค. 2013
Equatorial view of 3D GRMHD Simulation of Accretion disk in SANE state
Shows equatorial view of 3D simulation of SANE accretion disks with a steady accumulation of magnetic flux which remains much lower than the saturation value and causing no eruptions of magnetic flux and is characterized by steady accretion. The colors are density contours in logarithmic scale. The time shown at the top is in units of r_g/c, where r_g is the gravitational radius.
มุมมอง: 12
วีดีโอ
3D GRMHD Simulation of Accretion disk in Standard and Normal Evolution (SANE) state
มุมมอง 15วันที่ผ่านมา
Shows 3D simulation of SANE accretion disks with a steady accumulation of magnetic flux which remains much lower than the saturation value and causing no eruptions of magnetic flux and is characterized by steady accretion. The colors are density contours in logarithmic scale. The time shown at the top is in units of r_g/c, where r_g is the gravitational radius.
Equatorial view of 3D GRMHD Simulation of Accretion disk in Intermediate state
มุมมอง 5วันที่ผ่านมา
Shows equatorial view of 3D simulation of intermediate state accretion disks with an accumulation of magnetic flux but not reaching saturation and causing lesser eruptions of magnetic flux compared to MAD state. The colors are density contours in logarithmic scale. The time shown at the top is in units of r_g/c, where r_g is the gravitational radius.
3D GRMHD Simulation of Accretion disk in Intermediate state
มุมมอง 7วันที่ผ่านมา
Shows 3D simulation of intermediate state accretion disks with an accumulation of magnetic flux but not reaching saturation and causing lesser eruptions of magnetic flux compared to MAD state. The colors are density contours on a logarithmic scale. The time shown at the top is in units of r_g/c, where r_g is the gravitational radius.
Equatorial view of 3D GRMHD Simulation of Accretion disk in Magnetically Arrested Disk (MAD) state
มุมมอง 164วันที่ผ่านมา
Shows equatorial view of 3D simulation of MAD accretion disks with an accumulation of magnetic flux reaching saturation and causing eruptions of magnetic flux. The colors are density contours in logarithmic scale. The time shown at the top is in units of r_g/c, where r_g is the gravitational radius.
3D GRMHD Simulation of Accretion disk in Magnetically Arrested Disk (MAD) state
มุมมอง 48วันที่ผ่านมา
Shows 3D simulation of MAD accretion disks with an accumulation of magnetic flux reaching saturation and causing eruptions of magnetic flux. The colors are density contours in logarithmic scale. The time shown at the top is in units of r_g/c, where r_g is the gravitational radius.
2D GRMHD Simulation of Accretion disk in Standard and Normal Evolution (SANE) state
มุมมอง 7วันที่ผ่านมา
Shows 2D simulation of SANE accretion disks with a steady accumulation of magnetic flux which remains much lower than the saturation value and causing no eruptions of magnetic flux and is characterized by steady accretion. The colors are density contours in logarithmic scale and white lines are magnetic field lines. The time shown at the top is in units of r_g/c, where r_g is the gravitational ...
2D GRMHD Simulation of Accretion disk in Intermediate state
มุมมอง 23วันที่ผ่านมา
Shows 2D simulation of intermediate state accretion disks with an accumulation of magnetic flux but not reaching saturation and causing lesser eruptions of magnetic flux compared to MAD state. The colors are density contours in logarithmic scale and white lines are magnetic field lines. The time shown at the top is in units of r_g/c, where r_g is the gravitational radius.
2D GRMHD Simulation of Accretion disk in Magnetically Arrested Disk (MAD) state
มุมมอง 83วันที่ผ่านมา
Shows 2D simulation of MAD accretion disks with an accumulation of magnetic flux reaching saturation and causing eruptions of magnetic flux. The colors are density contours in logarithmic scale and white lines are magnetic field lines. The time shown at the top is in units of r_g/c, where r_g is the gravitational radius.
k Nearest Neighbour (k NN) Theory | Machine Learning Concepts
มุมมอง 182 หลายเดือนก่อน
This video talks about the theory behind classification using kNN algorithm and the measure of distance between any two points. It introduces concept of various types of distance that are used in inferring the nearest neighbours to an example. Calculations are done for an example of Euclidean distance. The concept of weighted distance is also introduced.
Linear regression Hands On in python | Machine Learning Concepts
มุมมอง 942 หลายเดือนก่อน
This video solves a Linear Regression problem using python and measures the performance of the model using R squared accuracy. It includes the following: 1. Basics of python packages 2. How to read datasets 3. Preprocessing steps 4. Test Train Split 5. Model Building 6. Checking performance
Conditional Probability | Machine Learning Concepts
มุมมอง 143 หลายเดือนก่อน
This video talks about Conditional probability which is an important concept in Probability and is used in Naive Bayes algorithm and others in Machine Learning. It also talks about independent events and dependent events.
Concept of Entropy and Information gain in Decision Tree | Detailed Calculation with examples | ML
มุมมอง 1013 หลายเดือนก่อน
This video explains how to construct decision trees using entropy and information gain. We see an example on how to calculate entropy and information gain.
Bayesian Network example | Alternative Solution of Question 4 Week 4
มุมมอง 713 หลายเดือนก่อน
This video shows an example of Bayesian Network which can be solved using Bayes Theorem.
R squared measure of Accuracy | Machine Learning Concepts
มุมมอง 233 หลายเดือนก่อน
R squared measure of Accuracy | Machine Learning Concepts
Maximum A Posteriori (MAP) Hypothesis | Calculation with examples | Machine Learning Concepts
มุมมอง 433 หลายเดือนก่อน
Maximum A Posteriori (MAP) Hypothesis | Calculation with examples | Machine Learning Concepts
Introduction to Machine learning NPTEL - Week 7
มุมมอง 2953 หลายเดือนก่อน
Introduction to Machine learning NPTEL - Week 7
Gini Impurity calculation with example in Decision Tree | Machine Learning Concepts
มุมมอง 543 หลายเดือนก่อน
Gini Impurity calculation with example in Decision Tree | Machine Learning Concepts
References for Machine Learning, Deep Learning and Artificial Intelligence
มุมมอง 623 หลายเดือนก่อน
References for Machine Learning, Deep Learning and Artificial Intelligence
Difference between Classification and Regression Decision trees with examples | Machine Learning
มุมมอง 253 หลายเดือนก่อน
Difference between Classification and Regression Decision trees with examples | Machine Learning
Basic introduction to Probability | Machine Learning Concepts
มุมมอง 1673 หลายเดือนก่อน
Basic introduction to Probability | Machine Learning Concepts
Convolutional Neural Networks CNN explained with hands on in python | Deep Learning Concepts
มุมมอง 273 หลายเดือนก่อน
Convolutional Neural Networks CNN explained with hands on in python | Deep Learning Concepts
Kernel Functions with examples | Support Vector Machines (SVM) |Machine Learning concepts
มุมมอง 423 หลายเดือนก่อน
Kernel Functions with examples | Support Vector Machines (SVM) |Machine Learning concepts
Support Vector Machines (SVM) and Idea of a Kernel with examples | Machine Learning Concepts
มุมมอง 383 หลายเดือนก่อน
Support Vector Machines (SVM) and Idea of a Kernel with examples | Machine Learning Concepts
Introduction to Machine Learning NPTEL - Week 6
มุมมอง 2873 หลายเดือนก่อน
Introduction to Machine Learning NPTEL - Week 6
Principal Component Analysis | Theory with examples | Machine Learning concepts
มุมมอง 394 หลายเดือนก่อน
Principal Component Analysis | Theory with examples | Machine Learning concepts
Feature Selection | Forward and Backward Propagation | Correlation | Machine Learning
มุมมอง 134 หลายเดือนก่อน
Feature Selection | Forward and Backward Propagation | Correlation | Machine Learning
Gradient Descent for Logistic Regression with Derivation | Machine Learning concepts
มุมมอง 484 หลายเดือนก่อน
Gradient Descent for Logistic Regression with Derivation | Machine Learning concepts
Log Likelihood function for Logistic Regression | Machine Learning concepts
มุมมอง 394 หลายเดือนก่อน
Log Likelihood function for Logistic Regression | Machine Learning concepts
Bernoulli Distribution with coin toss experiment | Statistics | Machine Learning
มุมมอง 444 หลายเดือนก่อน
Bernoulli Distribution with coin toss experiment | Statistics | Machine Learning
analogous to black holes maybe somewhat? very cool!
Hello Rohan, I had cleared the exam with elite silver.The way you explained confusion matrix and probability is very good. Thanks a lot
That's great to hear! Glad the video helped.
Exam khatm na , sir ?
Taylor Michael Thomas Helen Perez Jason
Reinforcement Learning - ML feedback-based approach where agent learns to make decision by interacting with environment thru Trial and error process. Example: Dog fetching a Ball Agent: Dog Action (it takes) : Pick Ball Reward: Positive feedback, treats, praise etc. If not pick ball, no reward (ie. punishment). Therefore, Dog overtime learns thru trial-error and aims to maximize rewards.
Thank you Rohan sir
Hello sir,would like to connect with you regarding ML.
great explanation
You explained that so clearly , it really helped me grasp the concept. I would really appreciate connecting with you on LinkedIn.
Needs clear explanation
Presentation, Notes, and Codes are available at the following link: drive.google.com/drive/u/1/folders/1GiXH6e8rC0qCZ0c5ATiiRkXBdtBuBZGj
Helpful video
Thanks!
Presentation, Notes, and Codes are available at the following link: drive.google.com/drive/u/1/folders/1GiXH6e8rC0qCZ0c5ATiiRkXBdtBuBZGj
Presentation, Notes, and Codes are available at the following link: drive.google.com/drive/u/1/folders/1GiXH6e8rC0qCZ0c5ATiiRkXBdtBuBZGj
Bhaiya u are writing too small in this session please increase the font if possible from next time plz
Sure, will do
Some of the terminology i couldn't be able to understand in lectures provided
which terminologies?
r u a student???
Yes
Excellent Jii