Machine Learning

CS
Craw Security
Last Update February 25, 2021
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About This Course

The machine learning we study about such type of machine which takes the raw data from their environment and learn from these data and apply this information in future need. Machine learning is a part of artificial intelligence that uses delay life data to learn themselves. Machine learning uses the techniques of pattern recognition. The machine observes the thing in a patterned manner and tries to understand these patterns according to their learning techniques. The machine learns and collects the knowledge without using any kind of algorithms. In the early days, machine learning is a very good field for a career opportunity. nowadays many organization works on machine learning programs and hire the employees for it. For machine learning and artificial intelligence, the most used languages are R language and python. Machine learning also used the concept of IoT.

Machine Learning

Machine Learning Online Training Course Content

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01 : Introduction to Machine Learning​
02 : Linear Regression​
03 : Multiple Linear Regression
04 : Gradient Descent
05 : Saving Model to a File
06 : Dummy Variables
07 : Train-Test-Split
08 : Logistic Regression
09 : Multiple Logistic Regression
10 : Decision Tree
11 : Random Forest
12 : K-fold Cross Validation
13 : SVM
14 : K-Means Clustering
15 : Naïve Bias
16 : One-Hot Encoding
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Online Machine Learning Course Program

Machine learning is a part of artificial intelligence that uses delay life data to learn themselves

Why Choose Machine Learning Course Training

Machine Learning is stretched and penetrated in the daily routine of us that even we don’t notice, the career in machine learning have the high and better opportunity as the world needs it and is getting higher in demand because the human being is getting dependent on the machines as technologies growing day per day, and that’s the reason why students who are just worrying about their career and have any interest in Artificial Intelligence going for machine learning course as it increases their package as well as get their market value higher. Craw Cyber Security provides this course training and certifications as affordable and cheap as compare to other institutes domestically or globally.

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Frequently Asked Questions

Machine Learning Training Course Program

Machine learning is an area of artificial intelligence and computer science that covers topics such supervised learning and unsupervised learning and includes the development of software and algorithms that can make predictions based on data.

Machine learning is all about making computers perform intelligent tasks without explicitly coding them to do so. This is achieved by training the computer with lots of data. Machine learning can detect whether a mail is spam, recognize handwritten digits, detect fraud in transactions, and more.

machine learning remains a relatively 'hard' problem. There is no doubt the science of advancing machine learning algorithms through research is difficult. It requires creativity, experimentation and tenacity. The difficulty is that machine learning is a fundamentally hard debugging problem.

we have covered some of the the most important machine learning algorithms for data science: 5 supervised learning techniques- Linear Regression, Logistic Regression, CART, Naïve Bayes, KNN. 3 unsupervised learning techniques- Apriori, K-means, PCA

On one hand, data science focuses on data visualization and a better presentation, whereas machine learning focuses more on the learning algorithms and learning from real-time data and experience

1)Naïve Bayes Classifier Algorithm
2)K Means Clustering Algorithm
3)Support Vector Machine Algorithm
4)Apriori Algorithm
5)Linear Regression Algorithm
6)Logistic Regression Algorithm

Requirements

  • Basic IT Skills
  • No Linux, programming knowledge required.
  • Computer with a minimum of 4GB ram/memory.
  • Operating System: Windows / OS X

Target Audience

  • Employee
  • Business Analysis
  • Students

Curriculum

40h

MODULE 01 :Introduction to Machine Learning​

MODULE 02 : Linear Regression​

MODULE 03 : Multiple Linear Regression

MODULE 04 : Gradient Descent

MODULE 05 : Saving Model to a File

MODULE 06 : Dummy Variables & One-Hot Encoding

MODULE 07 : Train-Test-Split

MODULE 08 : Logistic Regression

MODULE 09 : Multiple Logistic Regression

MODULE 10 : Decision Tree

MODULE 11 : Random Forest

MODULE 12 : K-fold Cross Validation

MODULE 13 : SVM

MODULE 14 : K-Means Clustering

MODULE 15 : Naïve Bias

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machine learning

14,999.0021,500.00

30% off
Level
Intermediate
Duration 40 hours
Language
English Hindi

Material Includes

  • Books
  • Toolkit
  • Videos
  • Softwares

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