Machine Learning

Data Analysis, Cleaning and visualisation Exploratory Data Analysis : Data Cleaning and Preprocessing Data Visualization Techniques Feature Extraction and Feature Selection What is Data Analysis? Data analysis is the process of looking through, purifying, manipulating, and modelling data to glean valuable information and insights.  Exploratory Data Analysis (EDA) is the process of analyzing and visualizing data to extract insights and patterns. It is an essential step in the machine learning pipeline that helps to identify data quality issues, understand the distribution of data, detect anomalies, and gain a deeper understanding of the relationships between variables.

Neural Network Perception and Backpropagation Concepts of Neural Networks Introduction, Neural network representation Perceptron Multi-Layer Perceptron (MLP) Convolutional Neural Networks (CNN) Recurrent Neural Networks (RNN) back propagation algorithm and Remarks An illustrative example of face recognition Advanced topics in artificial neural networks Artificial Neural Networks Definition   Neural networks are a type of machine learning that uses interconnected nodes to simulate the function of a human brain to solve complex problems. 

Reinforcement  Q-Learning and Markov Decision Processes  Reinforcement Learning Concepts Introduction,  Learning tasks Q-Learning and Deep Q-Learning Markov Decision Processes (MDP) Policy Gradient Methods Rewards and Actions,  Temporal Difference Learning Generalizing from examples, the  Relationship to Dynamic Programming  Reinforcement Learning Definition:  Reinforcement learning is a type of machine learning where an agent learns through trial and error to achieve a specific goal by maximizing a reward function.  

Convolutional  and  Recurrent Neural Networks What is Deep Learning? Deep learning is a subset of machine learning that uses deep neural networks to extract complex features from data.  Introduction to Deep Learning Deep Neural Networks (DNN) Convolutional Neural Networks (CNN) Recurrent Neural Networks (RNN) Autoencoders Generative Adversarial Networks (GAN)

Text Preprocessing and Sentiment Analysis  Natural Language Processing Concepts Introduction Text Preprocessing Bag-of-Words and Word Embeddings Sentiment Analysis Recommender Systems Collaborative Filtering Content-Based Filtering Hybrid Recommender Systems NLP (Natural Language Processing) Definition NLP is a subset of machine learning that focuses on the processing and understanding of human language.

 Interview Questions and Answers in Machine Learning Questions and Answers in Machine Learning :  Questions and answers in machine learning are focused on addressing common questions and issues that arise when working with machine learning algorithms .  How does machine learning differ from conventional programming, and what is it? Ans : Artificial intelligence's area of machine learning gives computers the ability to learn from data and make predictions or judgements without having to be explicitly programmed. Traditional programming involves manually writing code that tells the machine what to do, whereas, in Machine Learning, the machine automatically learns patterns from the data.