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Saptarsi Goswami @UCLaffR2o8SYTS891uyTBs_g@youtube.com

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06:50
Advanced Machine Learning Course (Introductory Video)
03:12
S4DS Ideathon
16:08
GAN using Tensorflow
20:47
GAN - A simple introduction
22:08
Genetic Algorithm Overview
45:38
Data warehouse Overview
56:31
Permutation and Combination with repetition
07:18
Insertion, Deletion, Update Anomaly
16:34
Smote with Python
23:21
Discrete Maths Counting Sum, Product, Inclusion and Exclusion
34:20
Discrete Maths Set, Functions, Composite Function
15:46
Relational Algebra Select, Project, Union
33:59
Relational Database Management Relation, Schema, Instance, Keys
06:26
Oracle LiveSQL Overview
36:34
DBMS SQL Tutorial
26:23
Python Lists
10:04
Python List Class 1
01:00:07
Data Mining Class 2021 01 06 Clustering
06:11
How to store documents in google drive for sharing
23:13
K Means and Hclust using R Programming
57:09
AI State Space Search, heuristic function
13:37
A Tutorial on Semi Supervised Learning
16:56
Applying kNN using R
53:34
Improving Hill Climbing and Simulated Annealing
17:32
How to perform Linear Regression using R
12:56
How to use SMOTE, Borderline SMOTE, ADASYN to handle class imbalance
08:30
How to use VGG16 as a pre-trained model in 8 minutes
14:32
Lec 23 CNN Lecture 8 VGGNet a brief introduction
17:34
Lec 22 CNN Architectures 2 AlexNet
05:56
How to scan your document in a pdf (In Hindi)
26:06
Hill Climbing Recap and Heuristic Search
15:05
Lec 21 CNN Architectures - I (LeNet5)
46:42
Basics of Classification and Evaluation
01:07:10
Class Basics and Constructor
14:15
Lec 20 Implementing basic CNN using TensorFlow and Keras
13:37
Java Objects and Classes 1
41:29
Java - Decision and Iterations
14:43
Lecture 19 CNN Pooling
17:38
Lec 18 Understanding Convolution (CNN Lecture 2)
19:27
Lec 17 Introduction to CNN
17:11
Lec 16 Weight Initialization and Batch Normalization
09:42
Lec 15: Regularization using Dropout (Keras)
14:45
Lec 14 Regularization Early Stopping Hands-on using Keras
08:59
Lec 13 Regularization Part 2 (Data Augmentation)
16:12
Lec 12 Introduction to Regularization
20:56
Collaborative Filtering (Memory Based)
14:00
Introduction to Recommendation System
16:37
Lec 11 Comparing Adam, RMSProp, SGD, Adagrad on Fashion MNIST
15:49
Lec 10 RMSProp, Adam and other optimizers
12:56
tSNE with Python
13:52
Lec 9 AdaGrad and AdaDelta
03:48
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21:07
Lec 8 Gradient Descent with Momentum
09:04
Lec 7 Regression using Neural Network as Keras and Tensorflow
11:35
Lec 6 Neural Network based Binary Classifier using TensorFlow and Keras
15:08
Mahalanobis Distance
19:36
Lec 5 Loss Function - Neural Network
01:22:53
Classifiers, Decision Tree and Ensemble B.P.Poddar 4th June 2020
07:39
Comparing two algorithms statistical test
10:08
Feature Selection using 1 Way ANOVA or F-Test in 10 Minutes