Build A Full CNN Aritifical Intelligence App within 30 minutes in Python: Data science

Rakesh Chinta, CEO NAG CORP, Harvard University, Google

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12 Videos (40m)
    • Welcome to the course

      1:10
    • Machine learning intro

      1:54
    • Writing our classifier

      2:52
    • Explaining the libraries required

      3:03
    • What will we do

      1:38
    • The process function

      3:54
    • Importing the libraries

      3:02
    • Building our convnet

      4:29
    • Softmax and reggresion code

      2:39
    • Setting the test and training data

      3:15
    • Fitting the data into our model

      2:26
    • Conclusion and finishing up the project

      9:21

About This Class

In machine learning, a convolutional neural network (CNN, or Convnet) is a class of deep, feed-forward artificial neural networks that has successfully been applied to analyzing visual imagery. ... CNN's use relatively little pre-processing compared to other image classification algorithms.

Why learn Machine learning?

  • Machine learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of machine learning
  • The machine learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period

What are the course objectives?A form of artificial intelligence, machine learning is revolutionizing the world of computing as well as all people’s digital interactions. By making it possible to quickly, cheaply and automatically process and analyze huge volumes of complex data, machine learning is critical to countless new and future applications. Machine learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.

This Machine Learning online course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in machine learning. The demand for machine learning skills is growing quickly. The median salary of a Machine Learning Engineer is $134,293 (USD), according to payscale.com.

What skills will you learn with our Machine Learning Course?

By the end of this Machine Learning course, you will be able to accomplish the following: 

  • Master the concepts of supervised and unsupervised learning
  • Gain practical mastery over principles, algorithms, and applications of machine learning through a hands-on approach which includes working on 28 projects and one capstone project.
  • Acquire thorough knowledge of the mathematical and heuristic aspects of machine learning.
  • Understand the concepts and operation of support vector machines, kernel SVM, naive bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
  • Comprehend the theoretical concepts and how they relate to the practical aspects of machine learning.
  • Be able to model a wide variety of robust machine learning algorithms including deep learning, clustering, and recommendation systems

Who should take this Machine Learning Training Course?

There is an increasing demand for skilled machine meaning engineers across all industries, making this Machine Learning certification course well-suited for participants at the intermediate level of experience. We recommend this Machine Learning training course for the following professionals in particular:

  • Developers aspiring to be a data scientist or machine learning engineer
  • Analytics managers who are leading a team of analysts 
  • Business analysts who want to understand data science techniques
  • Information architects who want to gain expertise in machine learning algorithms 
  • Analytics professionals who want to work in machine learning or artificial intelligence
  • Graduates looking to build a career in data science and machine learning
  • Experienced professionals who would like to harness machine learning in their fields to get more insights

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Rakesh Chinta

CEO NAG CORP, Harvard University, Google

Rakesh Naga Chinta is an Entrepreneur, SDE Intern at Google, Strategic Business Analyst, Author of several best-selling books.

A Harvard Alumni, with a burning passion for problem-solving and Entrepreneurship.

Previously worked as Software Engineering GSOC intern at google, Now is running several startups and ventures: where his skills are tested and sharpened every single day.

CEO and...

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