Torrent details for "Professional Certificate in Machine Learning"    Log in to bookmark

wide
Torrent details
Cover
Download
Torrent rating (0 rated)
Controls:
Category:
Language:
English English
Total Size:
10.61 GB
Info Hash:
c81cdc7225543d7fe979518ac28ee610c755b53d
Added By:
Added:  
26-05-2021 06:08
Views:
635
Health:
Seeds:
2
Leechers:
4
Completed:
63
wide




Description
wide
Image error
Description

Academy of Computing & Artificial Intelligence proudly presents you the course “Professional Certificate in Data Mining & Machine Learning“.m

It all started when the expert team of The Academy of Computing & Artificial Intelligence [ACAI] (PhD, PhD Candidates, Senior Lecturers , Consultants , Researchers) and Industry Experts . hiring managers were having a discussion on the most highly paid jobs & skills in the IT/Computer Science / Engineering / Data Science sector in 2020.

To make the course more interactive, we have also provided a live code demonstration where we explain to you how we could apply each concept/principle [Step by step guidance]. Each & every step is clearly explained. [Guided Tutorials]

“While artificial intelligence (AI) is the broad science of mimicking human abilities, machine learning is a specific subset of AI that trains a machine how to learn. Watch this video to better understand the relationship between AI and machine learning. You’ll see how these two technologies work, with useful examples and a few funny asides.”

Course Learning Outcomes

To provide a solid awareness of Supervised & Unsupervised learning coming under Machine Learning

Explain the appropriate usage of Machine Learning techniques.

To build appropriate neural models from using state-of-the-art python framework.

To build neural models from scratch, following step-by-step instructions.

To build end – to – end effective solutions to resolve real-world problems

To critically review and select the most appropriate machine learning solutions

python programming is also inclusive.

Requirements

   A computer with internet connection
   Passion & commitment

At the end of the Course you will gain the following

# Learn to Build 500+ Projects with source code

# Strong knowledge of Fundamentals in Machine Learning

# Apply for the Dream job in Data Science

# Gain knowledge for your University Project

   Setting up the Environment for Python Machine Learning
   Understanding Data With Statistics & Data Pre-processing
   Data Pre-processing – Scaling with a demonstration in python, Normalization , Binarization , Standardization in Python,feature Selection Techniques : Univariate Selection
   Data Visualization with Python -charting will be discussed here with step by step guidance, Data preparation and Bar Chart,Histogram , Pie Chart, etc..
   Artificial Neural Networks with Python, KERAS
   KERAS Tutorial – Developing an Artificial Neural Network in Python -Step by Step
   Deep Learning -Handwritten Digits Recognition [Step by Step] [Complete Project ]
   Naive Bayes Classifier with Python [Lecture & Demo]
   Linear regression
   Logistic regression
   Introduction to clustering [K – Means Clustering ]
   K – Means Clustering


What if you have questions?

we offer full support, answering any questions you have.

There’s no risk !

Who this course is for:

   Anyone who is interested of Data Mining & Machine Learning

Who this course is for:

   Anyone who wish to start a career in Machine Learning

Requirements

   Computer & Internet Connection

Last Updated 5/2021

  User comments    Sort newest first

No comments have been posted yet.



Post anonymous comment
  • Comments need intelligible text (not only emojis or meaningless drivel).
  • No upload requests, visit the forum or message the uploader for this.
  • Use common sense and try to stay on topic.

  • :) :( :D :P :-) B) 8o :? 8) ;) :-* :-( :| O:-D Party Pirates Yuk Facepalm :-@ :o) Pacman Shit Alien eyes Ass Warn Help Bad Love Joystick Boom Eggplant Floppy TV Ghost Note Msg


    CAPTCHA Image 

    Anonymous comments have a moderation delay and show up after 15 minutes