Generative Adversarial Network (GAN)
Deep learning model with two NNs — Generator & Discriminator — that compete to create realistic fake data.
“Generator fake data banata hai, Discriminator usse real/fake pehchanta hai.”
Noise → Generator → Fake Data → Discriminator → Real/Fake
Components:
1️⃣ Generator: makes fake data (tries to fool D)
2️⃣ Discriminator: checks data (real or fake)
Working:
G generates fake samples
D detects fake vs real
Both train together →
🧠 Recurrent Neural Network (RNN)
A neural network for sequential data (time series, speech, text).
It has memory of past inputs to affect current output.
Simple: “RNN past data yaad rakh kar next output predict karta hai.”
x1 → x2 → x3 → ...↓ ↓ ↓
h1 → h2 → h3 → ...
↓ ↓ ↓
y1 y2 y3
Stepwise:1️⃣ Input – Sequential data (text/audio)
2️⃣ Hidden Layer – Current input + previous hidden state
Eq: hₜ = f(Wxₜ + Uhₜ₋₁ + b)
3️⃣
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Explain in Detail Concept Of Gene Therapy
The term direct or vector less transfer of DNA is used when the foreign DNA is directly introduced into the genome. (a) Electroporation : Electroporation basically involves the use of high field strength, electrical impulses to reversibly permeabilize the cell membranes for the uptake of DNA. This technique can be used for the delivery of DNA into intact plant cells and protoplasts. Now-a-days, intact cells, callus cultures and immature embryos can be used with suitable pre-and post-electroporation...
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U.S. law comes from four sources: constitutional (from federal/state constitutions), statutory (laws passed by legislatures), administrative (rules by agencies like EPA), and case law (judge-made law based on precedent). Common law relies on stare decisis to ensure consistency. Substantive law defines rights; procedural law enforces them. Civil law resolves private disputes; criminal law punishes offenses....