Best Machine learning Training Institute In Noida
Inovi Technologies This Machine learning Training in Inovi Technologies is the best course to prefer in this lucrative world. Machine learning is a science to get computer to work without explicitly programmed. In the last decade, machine learning has given us a very good understanding of self-driving cars, practical speech recognition, effective web search and human genome. Learning machine is so widespread today that you probably used it dozens of times without knowing it. Many researchers also think that this is the best way to progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and apply them and get practice to work for them. More importantly, you will not only learn about the theoretical bases of learning, but also get practical information to apply these techniques in a quick and powerful way to new problems. Finally, you will learn about some of the best practices of Silicon Valley in innovation because this machine is related to learning and AI.
This course offers a comprehensive introduction to machine learning, data mining and identification of statistical patterns. Subjects include: (i) Supervised learning (parametric / non-parametric algorithms, support of vector machines, kernels, neural networks). (ii) Unheard Education (clustering, reduction in dimension, theorem system, deep learning). (iii) Best Practices in Machine Learning (Bias / Vision Principles), Innovation Process in Machine Learning and AI). The curriculum will be attracted by many case studies and applications so that you will learn to apply learning algorithms to create smart robots (perception, control), text understanding (web search, anti-spam), computer visualization, medical informatics. Audio, database mining and other fields.
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Module01: Regression Techniques
1.Random Forest Regression
2. Simple Linear Regression
3. Multiple Linear Regression
4. Polynomial Linear Regression
6. Support Vector Regression
7. Decision Tree Regression
Module 2: Classification Techniques
1. K-Nearest Neighbors (KNN)
2. Support Vector Machine (SVM)
3. Kernel SVM
4. Naïve Bayes Classification
5. Decision Tree Classification
6. Random Forest Classification
7. Evaluating Classification Model Performance
Module 3:Natural Language Processing (NLP)
1. Basic of NLP
2. Language preprocessing Techniques
3. Auto summarizing the given text document
4. K-Means Clustering
5. K-mini Batch Clustering
6. Build Pipeline View Project
7. Hierarchical Clustering
8. Jenkins to run script remotely
9. Elbow Method
10.Curve Smoothening Techniques
Module 4:Dimension Reduction Techniques
1. Docker Principal Component Analysis (PCA)
2. Linear Discriminant Analysis (LDA)
3. Basics of Numpy and panda
4. Reinforcement Learning
5. Association Rule Learning
6. Curve Smoothening Techniques
Module 5: Statistics Basics
1. Standard Deviation
2. Variance
3. Co-Variance
4. T-distribution
5. Pearson Correlation Coefficient (PCC)/ Correlation Coefficient
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Phone.No- +91-120-421-3880
EMail- info@inovitechnologies.com
Address:- F7 Sector-3 Noida UP 201301
