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Machine Learning & Deep Learning Online Live Class by Experts

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Machine Learning & Deep Learning Online Live Classes in Riffa | Free Demo Training

Machine Learning & Deep Learning - Syllabus, Fees & Duration

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

Download Syllabus - Machine Learning & Deep Learning
This syllabus is not final and can be customized as per needs/updates
 

    Course Highlights

  • Since 2001, Making IT Experts by Experts
  • Duration: 1000 Hours (Vary as per your skill)
  • Course Fees
  • Individual Live Classes (1:1)
  • Batch Classes @ Low Fees
  • Training on Your Time, Any Where
  • Access to Recorded Videos
  • Practical Internship on Projects
  • 100% Placement Support by our jobsNEAR.in
  • Training/Internship Certificate
  • Our Locations

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Machine Learning & Deep Learning Jobs in Riffa

Enjoy the demand

Find jobs related to Machine Learning & Deep Learning in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Riffa, chennai and europe countries. You can find many jobs for freshers related to the job positions in Riffa.

  • Machine Learning Engineer
  • Deep Learning Engineer
  • AI Engineer
  • Data Scientist
  • Computer Vision Engineer
  • NLP Engineer
  • Python AI Developer
  • AI Research Engineer
  • MLOps Engineer
  • AI Application Developer

Machine Learning & Deep Learning Internship/Course Details

Machine Learning & Deep Learning internship jobs in Riffa
Machine Learning & Deep Learning By the end of the course, participants will have the skills required to design, train, evaluate, and deploy machine learning and deep learning models, preparing them for rewarding careers in AI and data science in **Riffa**. . The **Machine Learning & Deep Learning** course in **Riffa** is a comprehensive program designed for students, software developers, and aspiring AI professionals who want to build intelligent systems using modern machine learning and deep learning techniques. The course covers Python programming, data preprocessing, supervised and unsupervised learning, neural networks, TensorFlow, Keras, computer vision, natural language processing (NLP), and model deployment. Through hands-on projects and real-world case studies, learners will gain practical experience in developing predictive models, image classification systems, recommendation engines, and AI-powered applications.

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