Create Virtual Env in Python
Run ML on AMD GPU
Machine Learning & Types:
Supervised Learning, SemiSupervised Learning, unsupervised Learning,
Reinforcement Learning, Generative AI
Terms:
AI vs ML vs DL, Activation Function, Bias/Sampling Bias, Conda, CNTK,
Overfitting, Underfitting, Optimizer, Large Language Model(LLM), Layer,
Learning Types, Loss Function, Matplotlib, Metrics,
Neuron, Neural Network, Tensor: Add
Vector & matrix, Dot Product, Tensor Reshaping stochastic gradient
descent (SGD) Tensorflow Variance
Code:
Opencv:
Draw rectangle around faces
speech_recognition:
Convert Voice to Text
OpenAI APIs:
Call openai APIs from code/Postman
ML Model
Code:
1. Calories Predictor during workout using:
DecisionTreeRegressor, Random Forest Regression model
2.
Filling Missing values using Imputator
Claude Code
Ollama: Open Source Model
Runner
ML Libraries
Keras(build Neural Networks):
keras, Comparison(Networks vs. Traditional ML Models(scikit-learn)),
Layers & APIs(Dense,
Convolutional..)
Code:
Classify grayscale images into(0 to 9),
Classify movie Review as +ve or -ve based on 50k review.
Pandas:
Introduction(series,
dataframes),
Conversion(dataframe to
numpy array),
Plots(Histograms, boxplot
and save in png file)
Functions: any(),
read_csv(), describe(), drop(), dropna(), head(), isNull(),
select_dtypes(), shape(), sum()
scikit-learn(build light weight models)
Introduction
Code:
Anomaly Detection using scikit learn
Functions:
train_test_split(), RandomForestRegressor(), fit()
Tensorflow
Langchain
Introduction
Terms: Message Types,
LangChainMessage Types
RAG (Retrieval-Augmented Generation)
RAG, RAG Pipeline, Code
RAG Pipeline Observability
Companies working in RAG Space
RAGAS(Retrieval Augmented Generation Assessment)
Introduction
Testing RAG using RAGAS
Protocols:
MCP(Model Context Protocol)