Login     Signup
   info@zetlantechnologies.com        +91-8680961847

Home   >   Machine Learning (ML)


Machine learning (ML) is a subfield of artificial intelligence (AI) that focuses on developing algorithms that allow computers to learn from data and improve their performance on specific tasks without being explicitly programmed. In essence, ML enables systems to analyze data, identify patterns, and make predictions or decisions based on that data


Key characteristics :


Course Details

1. Introduction to Machine Learning

  • What is Machine Learning?
  • Types of Machine Learning:
    • Supervised Learning
    • Unsupervised Learning
    • Reinforcement Learning
  • Applications of ML in Real-World Scenarios
  • Overview of Python Libraries for ML (NumPy, Pandas, Matplotlib, Scikit-Learn, TensorFlow, PyTorch)

  • Understanding Data: Features, Labels, Training & Testing Sets
  • Handling Missing Values and Outliers
  • Feature Scaling (Normalization & Standardization)
  • Encoding Categorical Variables
  • Data Visualization Techniques
  • Dimensionality Reduction (PCA, t-SNE, LDA)

  • Linear Regression
  • Multiple Linear Regression
  • Polynomial Regression
  • Ridge & Lasso Regression
  • Evaluation Metrics: RMSE, R² Score
  • Implementing Regression Models using Python

  • Logistic Regression
  • k-Nearest Neighbors (KNN)
  • Support Vector Machines (SVM)
  • Decision Trees
  • Random Forests
  • Naïve Bayes
  • Model Evaluation Metrics: Accuracy, Precision, Recall, F1-score, ROC Curve

  • Clustering Techniques:
    • k-Means Clustering
    • Hierarchical Clustering
    • DBSCAN
  • Association Rule Learning (Apriori, FP-Growth)
  • Anomaly Detection Techniques

  • Feature Selection Techniques
  • Hyperparameter Tuning (Grid Search, Random Search, Bayesian Optimization)
  • Cross-Validation Techniques
  • Handling Imbalanced Datasets

  • Introduction to Neural Networks
  • Forward & Backpropagation
  • Activation Functions
  • Introduction to Deep Learning Frameworks (TensorFlow, Keras, PyTorch)
  • Building and Training a Neural Network
  • Convolutional Neural Networks (CNNs) for Image Classification
  • Recurrent Neural Networks (RNNs) and LSTMs for Time Series & NLP

  • Introduction to Reinforcement Learning
  • Markov Decision Process (MDP)
  • Q-Learning & Deep Q Networks (DQN)
  • Policy Gradient Methods

  • Text Preprocessing (Tokenization, Lemmatization, Stopwords Removal)
  • Bag of Words, TF-IDF, Word Embeddings (Word2Vec, GloVe)
  • Sentiment Analysis
  • Named Entity Recognition (NER)
  • Transformer Models (BERT, GPT)

  • Model Deployment with Flask and FastAPI
  • Cloud Deployment (AWS, Google Cloud, Azure)
  • Building ML Pipelines
  • Introduction to MLOps


Fees Structure : 15500 INR / 180 USD
Total No of Class : 45 Video Class
Class Duration : 48:00 Working Hours
Download Feature : Download Avalable
Technical Support : Call / Whatsapp : +91 8680961847
Working Hours : Monday to Firday 9 AM to 6 PM
Payment Mode : Credit Card / Debit Card / NetBanking / Wallet (Gpay/Phonepay/Paytm/WhatsApp Pay)

Brochure       Buy Now       Sample Demo

Fees Structure : 22000 INR / 255 USD
Class Duration : 40 Days
Class Recording : Live Class Recording available
Class Time : Monday to Firday 1.5 hours per day / Weekend 3 Hours per day
Technical Support : Call / Whatsapp : +91 8680961847
Working Hours : Monday to Firday 9 AM to 6 PM
Payment Mode : Credit Card / Debit Card / NetBanking / Wallet (Gpay/Phonepay/Paytm/WhatsApp Pay)

Download Brochure       Pay Online

Information Technologies

Why People Like us!

For over a decade, we have been on a mission: helping everyone grow up in IT Industry. Today, we are asking that you join us.

Read More

More Info

About Us Contact Us Privacy Policy Terms & Condition Refund Policy FAQs & Help

Account

My Account Course Details Shopping Cart Wishlist Order History Payment Details

Contact

Address: Chennai, Tamilnadu, India

Email: info@zetlantechnologies.com

Phone: +91 8680961847

Payment Accepted

Zetlan Technologies, All right reserved.