Skill go
Machine Learning
Welcome to our Machine Learning Course in India! Join our 3-month self-paced training program for everyone: students, freshers, job seekers, working professionals, and entrepreneurs.
★★★★★ 5/5
- Trusted by 30k+ Students / Working Professionals
- Last updated 02/02/2025
Our Machine Learning Course in India, offered by SkillGo, provides an interactive online learning experience that simulates a classroom setting. This comprehensive 2-month program covers key concepts like supervised and unsupervised learning, MLOps, and Python programming. Gain hands-on experience with real-world projects such as IPL score prediction, rainfall forecasting, and spam SMS detection using industry-leading tools like TensorFlow, Keras, ChatGPT, and Amazon Sagemaker. Our dedicated placement support through the SkillGo job portal connects you with top hiring companies across India. Upon completion, earn certifications recognized by leading organizations, setting you on the path to a successful career in machine learning.
What You'll Learn in Machine Learning Courses?
- Data Preprocessing – How to clean, prepare, and transform raw data into a usable format for building machine learning models.
- Supervised Learning – Understanding algorithms like linear regression, decision trees, and support vector machines to make predictions based on labeled data.
- Unsupervised Learning – Learning techniques like clustering (e.g., K-means) and dimensionality reduction (e.g., PCA) to find patterns and insights from unlabeled data.
- Model Evaluation – How to evaluate the performance of machine learning models using metrics like accuracy, precision, recall, F1-score, and confusion matrices.
- Deep Learning – Getting familiar with neural networks and techniques like deep neural networks (DNN), convolutional neural networks (CNNs), and recurrent neural networks (RNNs) for more complex tasks like image recognition and natural language processing.
- Model Optimization and Tuning – Techniques for improving model performance, including hyperparameter tuning, regularization, and cross-validation to avoid overfitting and improve generalization.
Course Lessons
- What is Machine Learning?
- Understanding Supervised & Unsupervised Learning Machine Learning Intuition
- Real-world Applications of ML
- Overview of Vectors & Matrices
- Basic Matrix Operations (Addition, Subtraction, Multiplication, Transpose, Inverse)
- Understanding Regression & Representation
- Introduction to Cost Function
- Role of Cost Minimization
- Visualizing Cost Function
- Intuition Behind Gradient Descent
- Multivariate Linear Regression
- Introduction & Real-world Applications
- Understanding Classification
- Decision Boundaries & Model Intuition
- Logistic Cost Function
- Gradient Descent for Logistic Regression
- Multiclass Classification
- Understanding Overfitting & Underfitting
- Model Evaluation Techniques
- Regularization & Its Impact on Learning
- Bias & Variance in ML Models
- Error Analysis & Performance Optimization
- Basics & Intuition of Neural Networks
- Why Neural Networks?
- Model Structuring & Representation
- Sample Networks & Vectorization
- Neural Networks in Classification
- Introduction to Transfer Learning
- Overview of TensorFlow
- Key Features & Applications
- Introduction to Keras & TensorFlow Components
- Understanding Activation Functions
- in Building Simple & Multi-Class Neural Networks
- ITHUM TOWER - Sector 62, Noida, Uttar Pradesh
- info@skillgo.in
- +91 9235563477
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