• Need of Machine Learning
• Types of Machine Learning - Supervised, Unsupervised and Reinforcement Learning
• Applications of Machine Learning
• Concept of Supervised learning
• Types of Supervised learning: Classification and Regression
• Overview of Regression
• Types of Regression: Simple Linear Regression and Multiple Linear Regression
• Assumptions in Linear Regression and Mathematical Concepts behind Linear Regression
• Hands On
• Overview of the Concept of Classification
• Comparison of Linear regression with Logistic regression
• Mathematics behind Logistic Regression: Detailed Formulas and Functions
• Concept of Confusion matrix and Accuracy Measurement
• True positives rate, False positives rate
• Threshold evaluation with ROCR
• Hands on
• Overview of Tree Based Classification
• Concept of Decision trees, Impurity function and Entropy
• Concept of Impurity function and Information gain for the right split of node and
• Concept of Gini index and right split of node using Gini Index
• Overfitting and Pruning Techniques
• Stages of Pruning: Pre-Pruning, Post Pruning and cost-complexity pruning
• Introduction to ensemble techniques and Concept of Bagging
• Concept of random forests
• Evaluation of Correct number of trees in a random forest
• Hands on
• Introduction to probabilistic classifiers
• Understanding Naive Bayes Theorem and mathematics behind the Bayes theorem
• Concept of Support vector machines (SVM)
• Mathematics behind SVM and Kernel functions in SVM
• Hands on
• Overview of Unsupervised Learning
• Types of Unsupervised Learning: Dimensionality Reduction and Clustering
• Types of Clustering
• Concept of K-Means Clustering
• Mathematics behind K-Means Clustering
• Concept of Dimensionality Reduction using Principal Component Analysis (PCA)
• Hands on
• Overview of Concept of Natural Language Processing (NLP)
• Concepts of Text mining with Importance and applications of text mining
• Working of NLP with text mining
• Reading and Writing to word files and OS modules
• Text mining using Natural Language Toolkit (NLTK) environment: Cleaning of Text, Pre-Processing of Text and Text classification
• Hands on
• Overview of Deep Learning with neural networks
• Biological neural network Versus Artificial neural network (ANN)
• Concept of Perceptron learning algorithm
• Deep Learning frameworks and Tensor Flow constants
• Hands on
• Concept of Time series analysis, its techniques and applications
• Time series components
• Concepts of Moving average and smoothing techniques such as exponential smoothing
• Univariate time series models
• Multivariate time series analysis and the ARIMA model
• Time series in Python
• Sentiment analysis using Python (Twitter sentiment analysis Use Case) and Text analysis
• Hands on
Self-Paced Online Video
1 Year Unlimited Access
24 x 7 Expert Support
Real-life Case Studies
Learn at your Convenience
Pradyumna P Umarji
Manjunath M B
Harish Rama Chandran
This course on Machine Learning, which is one of the best Machine Learning Courses is designed by industry professionals that will help you get the best jobs in top MNCs. As part of this training you will be working on real-time projects and assignments that have immense implications in the real-world industry scenarios, thus helping you fast track your career effortlessly.
Tecklearn’s Machine Learning Certification will be awarded upon the completion of the course.
- To put your knowledge on into action, you will be required to work on industry-based projects that discuss significant real-time use cases.
- These projects are completely in-line with the modules mentioned in the curriculum and help you to clear the certification exam.
You will never miss a lecture at Tecklearn. Tecklearn provides recordings of each class so you can review them as needed before the next session.
Your access to the Support Team is for lifetime and will be available 24/7. The team will help you in resolving queries, during and after the course.
Post-enrolment, the LMS access will be instantly provided to you and will be available for lifetime. You will be able to access the complete set of previous class recordings, PPTs, PDFs, assignments. Moreover, the access to our 24x7 support team will be granted instantly as well. You can start learning right away.
Yes, the access to the course material will be available for lifetime once you have enrolled into the course.
All the instructors at Tecklearn are practitioners from the Industry with minimum 10-12 years of relevant IT experience. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating remain on our faculty.
Machine learning is nothing but an implementation of Artificial Intelligence that allows systems to simultaneously learn and improve from past experiences without the need of being explicitly programmed. It is a process of observing data patterns, collecting relevant information, and making effective decisions for a better future of any organization. Machine learning facilitates the analysis of huge quantities of data, usually delivering faster and accurate results to extract profitable benefits and opportunities.
The average machine learning salary, according to Indeed's research, is approximately $146,085 (an astounding 344% increase since 2015). The average machine learning engineer salary far outpaced other technology jobs on the list.
With online certification training you get the flexibility to learn on your own terms.
Major advantages are:
Access to Latest Course Curriculum
Connect with Instructors around the world
Real-life Projects & Case Studies
Lifetime Access & 24x7 support
The participants of our training should have:
• Fair understanding of Statistics and Mathematics basics
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