Ranjeet Ranjan Jha

#6 Relational Model & Relational Algebra Explained DBMS Full Lecture

Ranjeet Ranjan Jha

Advanced ER Model & Relational Model Explained DBMS Complete Guide

Ranjeet Ranjan Jha

Keys, Entity Types & Relationships in dbms

Ranjeet Ranjan Jha

#3 ER Model Explained in detail with examples Entity, Relationship & Mapping Constraints

Ranjeet Ranjan Jha

Complete Flow of Database Systems DBA, Data Models, ER Model, Relational Model & Architecture

Ranjeet Ranjan Jha

Database Fundamentals Purpose of DBMS, Components & Architecture

Ranjeet Ranjan Jha

#DL_26 Autoencoders , Encoder- Decoder, Architecture, Types, and Applications Deep Learning

Ranjeet Ranjan Jha

#DL 25 part3 Transformers Masterclass From Attention to ViT, BERT & GPT The Complete DL Revolution

Ranjeet Ranjan Jha

#DL 24 Transformers Part-2 Multi-Head Attention, Positional Encoding, Add & Norm Explained

Ranjeet Ranjan Jha

#DL 23Transformers for Vision & NLP ,a Complete Guide to Self-Attention and Image Feature& Modern AI

Ranjeet Ranjan Jha

#DL21 BPTT Explained Truncated BPTT, Vanishing & Exploding Gradients, LSTM Solution

Ranjeet Ranjan Jha

#DL 22 LSTM & GRU Gradient Flow Single-Layer vs Multi-Layer RNNs and Advanced RNN Variants

Ranjeet Ranjan Jha

#DL 20 RNN Backpropagation Through Time, Image Captioning (CNN+RNN), and Visual Question Answering

Ranjeet Ranjan Jha

#DL 19 Master (RNNs) Sequence Processing, Variants & Seq2Seq Explained with Language Modeling

Ranjeet Ranjan Jha

#DL 18 Residual Networks ExplainedBottleneck Blocks, Model Complexity & Transfer Learning with CNNs

Ranjeet Ranjan Jha

#DL17 Evolution of Deep CNN Alex Net, VGG, GoogleNet & ResNet Efficiency, Auxiliary Classifiers

Ranjeet Ranjan Jha

#DL 16 Designing CNN , AlexNet, ZFNet & VGG ImageNet Challenge, Params, Memory & FLOPs Explained

Ranjeet Ranjan Jha

#DL 15 Batch Normalization Explained CNNs & Fully Connected Networks (FCNNs) Made Simple

Ranjeet Ranjan Jha

#dl 14 Understanding CNNs & LeNet-5 Beginner-Friendly Deep Dive with Visuals & Math

Ranjeet Ranjan Jha

#DL13 Understanding Convolution 1D, 2D, 3D Feature Extraction, Receptive Field, Stride, & Padding

Ranjeet Ranjan Jha

#DL__12 FCN vs CNN Limitations, Activation Functions & Convolution Filters Explained

Ranjeet Ranjan Jha

#DL 11Backpropagation Explained Step-by-Step Neural Networks with Code

Ranjeet Ranjan Jha

# 10 Biological Neurons vs Artificial Neural Networks Backpropagation Made Simple

Ranjeet Ranjan Jha

# 9 Feed Forward Neural Network Explained Neural Networks for Beginners

Ranjeet Ranjan Jha

# 8 (SGD, Momentum, RMSProp, Adam) + Activation Functions & Feed Forward Neural Networks Explained

Ranjeet Ranjan Jha

#7 Stochastic Gradient Descent, Momentum & RMSProp Explained Simply Optimization in Deep Learning

Ranjeet Ranjan Jha

#6_Deep Learning Linear Classifier with Regularization Finding Gradients Explained

Ranjeet Ranjan Jha

#5 Deep Learning Linear Classifiers & Regularization Finding the Best Weights (W)

Ranjeet Ranjan Jha

# 4 Linear Classifiers & Loss Functions

Ranjeet Ranjan Jha

#3 Image Classification with KNN & Linear Classifiers (Part 2)

Ranjeet Ranjan Jha