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Advanced AI
AI Fundamentals
Applied AI
Generative Models
MLOPs
AWS
Reinforcement Learning
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Amazon Elastic Inference
Amazon SageMaker Data Labeling
Amazon SageMaker Data Wrangler
Amazon SageMaker Debugger
Amazon SageMaker Feature Store
Amazon SageMaker Model Deployment
Amazon SageMaker Model Training
Amazon SageMaker Notebooks
Apache MXNET
AWS
AWS Data Pipeline
AWS Data Pipeline Development
AWS Glue
AWS Model Deployment
AWS Snow Family
Chains
Components (Agents
Data Processing
Data sanity check
Data splits
DataBrew
Deep Learning
Deep Learning AMIs
Distributed Training
DLAMI
Embeddings
EMR
Encoding
Feature Engineering
Generative AI
Generative Models
Hugging Face Framework
Hyperparameter opt - Automatic Model Tuning
IG
Inference Speed
Integrated Gradient
Kinesis
Knowledge Graphs
Langchain (essential)
LangServe
Langsmith
Large Language Model Framework (LLM)
LIME
LLM
Machine Learning
Machine Learning Optimization
Memory Usage Optimization
Memory)
Missing values
Model Compression
Model Deployment
Model Efficiency
model interpretability and explainability
Model Monitoring and Scaling
OpenAI GPT
Outliers
Post-training Quantization
Prompt Engineering
Prompts
Python / Pyspark
Quantization
Quantization Techniques
Quantization-aware Training
Question Answering
RAG
Reinforcement Learning
Resource-Constrained Environments
S3 Lifecycle Rules
Sagemaker
Scaling
SHAP
Snowflake
Text Generation
Vector Databases
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Course 3 : Applied Statistics for DS
By
Bhupen
In
Advanced AI
Course 5 : Machine learning – using gradients
By
Bhupen
In
Advanced AI
Course 9 : Explainable Predictive ML Modeling
By
Bhupen
In
Advanced AI
Course 6 : Deep Learning – Primer (TF/Keras)
40h
By
Bhupen
In
Advanced AI
Course 7 : Conv nets, PTMs, Transfer Learning
By
Bhupen
In
Advanced AI
Course 2 : combine models (Ensemble)
3h
By
Bhupen
In
Advanced AI
Course 4 : Feature Engineering (Selection/Extraction)
3h
By
Bhupen
In
Advanced AI
Course 1 : Classical Machine Learning Algorithms
6h
By
Bhupen
In
Advanced AI
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