Artificial Intelligence Training
Artificial Intelligence also called as Machine Intelligence is the ability of computer systems to perform the tasks that generally require a human brain’s intelligence and logic (Natural Intelligence) like speech recognition, face recognition, visual perception, language translation, decision making, self-correction and more. It is all about designing machines that can ‘think’ because, with artificial intelligence, machines display performance of “cognitive” functions like problem-solving and learning which are normally performed by human beings. Its use is increasing day by day in the daily life and so it is being used by a lot of industries like business, gaming, media, finance, medicine, robotics, law, manufacturing, education and more. The ATM Machine is also an example of AI. AI field is constantly growing and evolving expanding human capabilities beyond our imagination. In this course, you will learn all the basic and advanced concepts of modern AI and also it’s applications.
AI is a technology breakthrough making it easy to perform tasks difficult for human beings to achieve. Artificial Intelligence is the future of technology and is being adopted by every company for delivering better products and services with more accuracy and efficiency. Machine learning professionals are increasingly needed by organizations because this industry is expected to grow from $ 1 billion to $ 9 billion by 2022. We help you in targeting the best jobs in this industry by giving you hands-on and detailed AI & Machine Learning knowledge with the best qualified and experienced trainers.
What will you learn out of this course?
Machine Learning Applications
Future of Machine Learning Missing Data and Categorical Data How to set up Your GitHub Account? Intuition and Dataset + Business Problem Description Intuition and Python Regression Template Intuition R-Squared Intuition and Adjusted R-Squared Intuition Intuition Intuition Intuition Learning of False Positives & False Negatives Intro to K-Means Clustering Evaluating the ANN and Improving the ANN Basic of TF
ARTIFICIAL INTELLIGENCE SYLLABUS
Splitting the Dataset into the Training set and Test set
Git Repository configuration
How to make Your First Git Commit and push Your First Commit to GitHub?
Step-by-Step Git and GitHub Workflow
Simple Linear Regression and Multiple Linear Regression
Polynomial Regression and Decision Tree Regression
Decision Tree Regression and Random Forest Regression
How to Evaluate Regression Models Performance?
Concepts of Interpreting Linear Regression Coefficient
Logistic Regression and Python Classification Template
K-NN and SVM
Decision Tree Classification and Random Forest Classification
Concepts of Confusion Matrix and Accuracy Paradox
CAP Curve and CAP Curve Analysis
Basic of Intuition and Random Initialization Trap
Selecting the Number Of Clusters
Intro to K-Means Clustering
Intuition and Hierarchical Clustering How Dendrograms Work
Study of Hierarchical Clustering Using Dendrograms and HC
Concept of Tuning the ANN
Computation Graph and Tensors
Understanding Image Processing and Images As Tensors
Intro to MNIST
Individual Neuron and Learning Regression
Concepts of Learning XOR and XOR Trained
Machine Learning Applications Future of Machine Learning
Missing Data and Categorical Data
How to set up Your GitHub Account?
Intuition and Dataset + Business Problem Description
Intuition and Python Regression Template
R-Squared Intuition and Adjusted R-Squared Intuition
Learning of False Positives & False Negatives
Intro to K-Means Clustering
Evaluating the ANN and Improving the ANN
Basic of TF
Artificial Intelligence Course Price: 18999* INR