Artificial Intelligence and Machine Learning
Artificial intelligence and Machine Learning is Gain expertise in one of the most fascinating and fastest growing areas of computer science through an innovative online program that covers fascinating and compelling topics in the field of Artificial Intelligence and its applications
Machine learning is a connected insight or arithmetic. It is a subfield of software engineering. This part gives a short presentation about the Machine learning, history of machine learning, sorts of issues and errands in machine learning and its calculations.
Toward the finish of this course, you will have the capacity to
- Identify potential zones of uses of Machine Learning & AI
- This course covers foundational concepts and hands-on learning of leading machine learning tools, such as Python and TensorFlow.
- Providing Handon experience on a real-time case study.
In Self Learning Artificial intelligence and Machine Learning, the results are truly intriguing, after this course, you ought to have a solid comprehension of machine learning and Artificial Intelligence with the goal that you can seek after any further and further developed learning.
Here we provide training through artificial intelligence and machine learning video tutorial so you are going to learn the course by your self and we provide all time support with your queries and the major course part is run by python programming for machine learning python program is well suited and we prefer machine learning python course because it is open source and easily understood by candidates than other programming languages.
Software & Tools
A learner will be using given software and tool during this course.
and other …
Candidate must have basic knowledge of any programing language & Mathematics
Software and Machine –
- Anaconda – https://www.anaconda.com/download/ (According to bit version 32 bit for 32 Machine and 64 bit for 64-bit machine)
- Python Libraries used (Most of them are already available in Anaconda, others we will install during the training)
- Recommended – Machine with 4GB RAM, i3 or above quad-core processor
- Requirement: Working Internet Connection throughout the training for participants.
In this Module we will cover, Introduction to AI and Machine Learning. Application of Machine Learning- Supervised, Unsupervised and Reinforcement Learning, Classification, Regression, Clustering, Anomaly Detection Recommendation, System Algorithms in Machine Learning and Introduction to Deep Learning
In this module you will be able to popup with Python Programming, Object of this Module to make a fearless Python Coder, You will get to learn, practices and implement use cases, Build expertise in python programming, after learning python you can quick start with AI & ML
In this module you will experience different tools for Statistics-
In this module you will learn about Statistics of Data- Data Variable, Mean, Mode, Median, Standard Deviation Variance, Correlation and Probability
- Session 9. Descriptive Statistics, Inferential Statistics, Variable, Median, Percentile, RFM
- Session 10. Variance, Standard Deviation and IQR, Chebyshev’s Theorem
- Session 11. Covariance, Correlation, Kurtosis, Skewness, Analyzing the Continuous and Categorical Data, Probability
- Session 12. Chi-Square Test & Prediction
Starting with Machine Learning Algorithms
In this module we will starting with Artificial Neural NetWorks
- Session 20. Possibility the survival of passenger in titanic- Model, Random Forest and Introduction to Artificial Neural Networks
- Session 21. Artificial Neural Networks, Architecture and Mathematical Modelling of Neural Network
- Session 22. Backpropagation algorithm
- Session 23. Backpropagation algorithm-Model
Here, are continue with ANN Example and Introduction with Image Processing
Here you are going to learn forecasting, time series
Here you will learn Unsupervised learning
In this module you will learn Natural Language Processing and It's Model
November 16, 2018 at 05:10 am
Amazingly done! It covers the major topics in machine learning and definitely a good way to get familiar for those that are new to the field. Andrew is outstanding in explaining the mathematical aspects of the Machine learning without alienating those that do not have a strong mathematical background.
November 16, 2018 at 05:04 am
Great course with lots of interesting and useful information. Glad that things like this exist and I would recommend this course to everyone who is interested in machine learning & AI.
November 16, 2018 at 04:56 am
It was very straightforward and for once I actually understood how all these concepts work. It was also great that it covered helpful tips for picking and "debugging" algorithms. Would definitely recommend if you want to be conversant in AI and ML and have a few programs you've created to look back at when you want to create a new ML algorithm for a project.
October 27, 2018 at 12:06 pm
Excellent course. Perfectly organized. Builds up from the basics to more advanced concepts. Perhaps the leading course to begin with and refresh your knowledge in Artificial Intelligence and Machine Learning.