Machine Learning & Deep Learning Training in Salem

Introduction to Machine Learning

• Introduction to Artificial Intelligence
• Machine Learning Fundamentals
• Types of Machine Learning
• Real-World Applications

Python for Machine Learning

• Python Basics
• NumPy
• Pandas
• Matplotlib & Seaborn

Data Preprocessing

• Data Cleaning
• Handling Missing Values
• Feature Scaling
• Encoding Categorical Data

Exploratory Data Analysis

• Data Visualization
• Correlation Analysis
• Feature Selection
• Outlier Detection

Supervised Learning

• Linear Regression
• Logistic Regression
• Decision Trees
• Random Forest
• Support Vector Machines (SVM)
• k-Nearest Neighbors (KNN)

Unsupervised Learning

• K-Means Clustering
• Hierarchical Clustering
• DBSCAN
• Principal Component Analysis (PCA)

Model Evaluation

• Train-Test Split
• Cross Validation
• Confusion Matrix
• Accuracy, Precision, Recall & F1 Score

Introduction to Deep Learning

• Artificial Neural Networks
• Perceptron
• Activation Functions
• Forward & Backpropagation

TensorFlow & Keras

• TensorFlow Basics
• Keras API
• Building Neural Networks
• Model Training & Evaluation

Deep Learning Architectures

• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (RNN)
• LSTM & GRU
• Transfer Learning

Computer Vision

• Image Classification
• Object Detection Basics
• Image Augmentation
• OpenCV Introduction

Natural Language Processing

• Text Preprocessing
• Tokenization
• Word Embeddings
• Text Classification

Model Deployment

• Model Serialization
• Flask/FastAPI Integration
• REST API Development
• Deployment Basics

Real-World Projects

• House Price Prediction
• Customer Churn Prediction
• Sentiment Analysis
• Image Classification System
• Face Mask Detection
• Recommendation System