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Machine Learning
Machine learning is a subfield of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computers to perform tasks without being explicitly programmed. Advanced machine learning & AI course in Kerala, primary goal of machine learning is to allow computers to learn from data and improve their performance over time.
Machine learning is a subset of artificial intelligence that aims at creating the mechanisms of learning from data not through programming. It lets computers build proficiency in tasks, and in the subsequent solving, it allows them to amplify the proficiency. So, join the Advanced machine learning & AI course in Kerala Trivandrum, The key characteristics of machine learning include. Data-driven Machine learning models are built from data and then traverse the patterns that exist in data without hard-coded programming. Adaptive learning can be change to accommodate new data, adaptability is vital in dynamic settings. Generalization is to design models that perform well on distinct unseen data and not the training data.
Learning from Data:
Machine learning systems learn from data patterns and examples rather than relying on explicit
Programming Adaptability:
Indeed, it is understood that over time, machine learning models can yaw out more data and increase the efficiency of their performance.
Probabilistic Output:
There is a variety of models of machine learning, which give probabilistic estimates, telling,the probability of the particular result
Scalability:
Big data can be solve with machine learning techniques because these models can be train in larger and more complicated sets, moreover, the machine learning models can be apply in many fields. Besides, they facilitate swift processes and identify patterns within sets of data as well as large amounts of information. Also, due to their flexibility, they can be integrate into various industries primarily of medical or financial specialties. Therefore, given the scalability and applicability of machine learning the area holds solving problems in the contemporary data-oriented world.
Application Diversity:
Machine learning has applications in almost all sectors ranging from image, natural language processing, healthcare, finance and many others.
Probabilistic Output:
A huge number of machine learning models yield probabilistic predictions which convey the odds of a certain event
Our course and internship program in Advanced machine learning & AI course in Kerala Trivandrum is the perfect learning ground to kick-start your new career. This is an ideal course whether you are a novice who wants a career as a machinic learning Expert or a professional who is looking for an added advantage in their line of work.
Introduction to Machine Learning – 6 hours
Basic Concepts in Statistics and Probability – 12 hours
Introduction to Python for Machine Learning – 8 hours
Data Collection and Cleaning – 10 hours
Explorator
Data Analysis (EDA) – 12 hours
Feature Engineering – 8 hours
Linear Regression – 14 hours
Polynomial Regression – 8 hours
Evaluation Metrics for Regression – 10 hours
Logistic Regression – 10 hours
Decision Trees and Random Forests – 16 hours
Support Vector Machines (SVM) – 10 hours
Evaluation Metrics for Classification – 10 hours
Unsupervised Learning – Clustering – 10 hours
Dimensionality Reduction (PCA) – 10 hours
Association Rule Learning – 8 hours
Cross-Validation – 10 hours
Grid Search and Random Search – 8 hours
Model Selection and Evaluation – 10 hours
Introduction to Neural Networks – 10 hours
Multilayer Perceptrons (MLP) – 10 hours
Convolutional Neural Networks (CNN) – 20 hours
Recurrent Neural Networks (RNN) – 14 hours
Introduction to Natural Language Processing (NLP) – 10 hours
Text Preprocessing – 10 hours
Word Embeddings – 10 hours
Text Classification with RNNs and LSTMs – 10 hours
Introduction to Reinforcement Learning – 10 hours
Q-Learning and Deep Q Networks (DQN) – 10 hours
Advanced Topics and Emerging Trends – 14 hoursCourse Recap and Final Project – 68 hours
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