Introduction to Classification Metrics What is ROC Curve? True Positive Rate and False Positive Rate Understanding AUC Drawing ROC Curve in Python ROC vs Precision-Recall Curve Threshold Tuning Use in Model Comparison Multi-class ROC Curves Interpretation Challenges Summary Introduction to Classification...

Introduction to Decision Tree Algorithm Tree Structure and Terminology Splitting Criteria (Gini, Entropy) Overfitting and Pruning Decision Tree Algorithm in Classification and Regression Implementation in Python Visualizing Decision Trees Applications in Industry Ensemble Methods (Random Forest, Boosting) Hyperparameter...

Introduction to Random Forest Algorithm Ensemble Learning Basics Working of Random Forest Algorithm Decision Trees in Random Forest Algorithm Feature Importance and Selection Implementing Random Forest in Python (scikit learn) Hyperparameter Tuning Evaluation Metrics (Accuracy, ROC, etc.) Use Cases (Finance, Healthcare, etc.) ...

Introduction to Deep Learning Difference Between ML and Deep Learning Neural Network Basics Activation Functions and Optimizers Feedforward vs Recurrent Neural Networks Convolutional Neural Networks (CNNs) Overfitting and Regularization Building a Deep Learning Model Step-by-Step Real-World Applications Future Scope ...

Introduction to TensorFlow Setting Up TensorFlow Environment TensorFlow Basics: Tensors and Operations Graphs and Sessions in TensorFlow Building a Neural Network Training and Evaluation Handling Datasets with tf.data TensorBoard for Visualization TensorFlow Lite and TensorFlow.js Case Study: MNIST Classification Best...

Introduction to Reinforcement Learning Key Terminology (Agent, Environment, Reward) Types of RL (Model-based vs Model-free) Markov Decision Process (MDP) Q-Learning Deep Q Networks (DQN) Policy Gradient Methods Exploration vs Exploitation Applications of RL Tools and Libraries Challenges in RL Future Directions ...

Introduction to Ensemble Learning What is Gradient Boosting? How Gradient Boosting Works Key Components (Loss Function, Weak Learners) Types: XGBoost, LightGBM, CatBoost Advantages of Gradient Boosting Limitations and Overfitting Risks Hyperparameter Tuning Performance Metrics Real-World Applications Summary ...

Introduction ML Engineer vs Data Scientist Role Overview: ML Engineer vs Data Scientist Education and Background Requirements Tools and Technologies Used Day-to-Day Responsibilities Data Handling and Modeling Business Impact and Focus Work Environment and Team Collaboration Which Role Is Right for You? Conclusion ...

Introduction to Natural Language Processing Text Classification Sentiment Analysis Machine Translation Chatbots and Virtual Assistants Speech Recognition Named Entity Recognition (NER) Question Answering Systems Text Summarization Language Modeling Real-World Use Cases Future Trends in NLP Introduction to Natural...

Introduction to Deep Learning Frameworks What is TensorFlow? What is Keras? History and Evolution Ease of Use and Flexibility Performance and Speed Model Building and Training Comparison Compatibility and Integration Community and Documentation Use Cases and Applications Summary and Final Verdict Introduction to...