# Python Machine Learning Advanced (Self-Paced)

Canonical URL: <https://training.sdfm.org/courses/advanced-machine-learning-online>

## Overview

This hands-on course builds the core machine learning and deep learning abilities employers look for. You’ll work with NLP, sentiment analysis, recommendation systems, PyTorch for convolutional neural networks, Facebook Prophet, and the latest YOLO models for computer vision.

Develop the skills to train advanced models and create Flask applications that power product recommendations, visual recognition, and market forecasting. This course strengthens your portfolio, supports real AI project development, and positions you for growth in ML and AI engineering roles.

## What you'll learn

- Build and deploy full-stack applications with Flask
- Implement collaborative and content-based recommendation engines
- Forecast trends using advanced time series modeling with Facebook Prophet
- Train and evaluate convolutional neural networks using PyTorch
- Perform real-time object detection in images and video streams with YOLO
- Apply NLP techniques to build effective sentiment analysis models

## Curriculum

### 1. NLP & Sentiment Analysis

#### Environment Setup & NLP Fundamentals

- VS Code environment configuration, NLP libraries installation
- Tokenization, stopword removal, stemming, lemmatization
- Text representation with Bag of Words and TF-IDF

#### Sentiment Analysis Project

- Logistic Regression for sentiment classification
- Data splitting, model evaluation metrics (accuracy, precision, recall, confusion matrix)

### 2. Recommendation Systems

#### Collaborative Filtering

- User-based and item-based filtering
- Cosine similarity for personalized recommendations

#### Content-Based Movie Recommender

- Vectorizing text using TF-IDF
- Implementing content similarity algorithms

### 3. Flask App for Recommendations

#### Building an ML-Powered Web App

- Flask basics and web serving
- Developing a recommendation system Flask app

### 4. Forecasting & Deep Learning

#### Time Series with Facebook Prophet

- Trend forecasting and visualization (e.g., market prices)

#### Deep Learning with PyTorch

- CNN basics, image classification using the CIFAR-10 dataset
- Model training, accuracy assessment, and confusion matrix interpretation

### 5. Object Detection

#### Real-Time Object Detection with YOLO

- Image detection and labeling with pretrained models
- Adapting YOLO models to video streams and real-time webcam input

## Pricing

**Tuition:** $1895