Difference Between Generative Ai and Ai | Brolly Academy
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In this we tried to explain Difference between Generative Ai And Ai funnily in Telugu !!
In this Generative Ai Course We cover
Introduction to Generative AI.
AI vs ML vs DL vs NLP vs Generative AI.
Generative AI principles.
What is the role of ML in Gen-AI.
Different ML techniques (Supervised, Unsupervised, Semi-supervised & Reinforcement Learning).
Applications in various domains.
Ethical considerations.
Module 2 : NLP & Deep Learning
-NLP essentials.
-Basic NLP tasks.
-Different text classification approaches.
-Frequency-based – Bag of words, TF-IDF, N-gram.
-Distribution Models – CBOW, Skipgram(Traditional approaches)and
-word2vec, Glove.
-Ensemble Methods (Random Forest, Gradient Boosting, AdaBoost) &
-Traditional Machine Learning Models – Naïve Bayes, Support Vector
-Machine (SVM), Decision Trees, Logistic Regression.
-Deep learning techniques – CNNs, RNNs, LSTMs, GRU and
Transformers.
Module 3 : Generative AI Models
Autoencoders.
VAE’s and applications.
GANs and it’s applications.
Different types of GANs and applications.
Module 4 : Language Models & Transformer Models
Different types of Language models
Applications of Language models
Transformers and its architecture
BERT, RoBERTa, GPT variations
Applications of transformer models
Module 5 : Prompt Engineering
What is Prompt Engineering
What are the different principles of Prompt Engineering
Types of Different Prompt Engineering Techniques
How to Craft effective prompts to the LLMs
Priming Prompt
Prompt Decomposition
Module 6 : Large Language Models
Generative AI lifecycle
What is RLHF
LLM pre-training and scaling
Different Fine-Tuning techniques
Module 7 : LLM's Embeddings
What are word embeddings
What is the use of word embeddings, where we can use it?
Word Embeddings – Word2Vec, GloVe and FastText
Contextual Embeddings – ELMo , BERT and GPT
Sentence Embeddings – Doc2Vec, Infersent, Universal Sentence
Encoder
Subword Embeddings – BPE(Byte Pair Encoding), Sentence Piece
Usecase of Embeddings.
Module 8 : Different Chunk Metrics
What is Chunking
What is the use of chunking the document
What are the traditional effective chunking techniques
What are the problems and limitations with traditional chunking
techniques?
How to overcome the limitations of Traditional chunking
Advanced Chunking Techniques:
1. Character Splitting
2. Recursive Character Splitting
3. Document based Chunking
4. Semantic Chunking
5. Agentic Chunking
Module 9 : RAG and Advanced RA with Langchain
What is RAG
What are the main components of RAG
High level architecture of RAG
How to Build RAG using external data sources
Advanced RAG
Module 10 : Langchain for LLMs
What is Langchain
What are the core concepts of Langchain
Components of Langchain
How to use Langchain agents
Module 11 : Vector Databases
● LlamaIndex
● What are Vector Databases
● Why do we prefer Vector Databases over Traditional Databases
● Different Types of Vector Databases: OpenSource and Close Source
● OpenSource: Chroma DB, Weaviate,Faiss,Qdrant
● Close-Source Vector Databases:Pinecone,ArangoDB,Cloud-Based
Solutions
Module 12 : Finetuning LLMs
Supervised Finetuning
Repurposing-Feature Extraction
Advanced techniques in Supervised Finetuning -PEFT -LoRA, QLoRA
Module 13 : LLMs Evaluation
Text based LLMs:
Automatic Evaluation: BULE Score, ROUGE Score, METEOR, BERT
Score.
Human Evaluation: Coherence, Factuality, Originality, Engagement
Image based LLMs:
Automatic Evaluation: Pixel-level metrics, FID (Frechet Inception
Distance), IS (Inception Score), Perceptual Quality Metrics,
Diversity Metrics.
Human Evaluation: Photorealism, Style, Creativity, Cohesiveness
Audio generation LLMs:
Automatic Evaluation: FAD (Frechet Audio Distance), IS (Inception
Score), Perceptual Quality Metrics – PAQM, PAQM – SNR (Signal-to-Noise Ratio), PAQM – PESQ (Perceptual Evaluation of Speech
Quality)
Human Evaluation:Perceptual Quality – PQ, PQ- Naturalness, PQFidelity, PQ- Musicality, Task Specific Evaluation.
Video Generation LLMs:
Automatic Evaluation: FVD (Frechet Video Distance), Inception
Score(IS), Perceptual Quality Metrics, Motion Based Metrics –
Optical Flow Error, Content-Specific Metrics.
Human Evaluation: Visual Quality, Temporal Coherence, Content
Fidelit.
Module 14 : LLMops
Module 15 : LLM's on Cloud
Module 16 : Different AI Tools
In this video we covered Difference Between Generative Ai and Ai
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