Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
1. Introduction | |
What do we understand when we talk about the term Machine-Learning in today’s perspective of Technology? What can we achieve through means of complex algorithms? | |
Simple answer to these questions comes from the need to recognize patterns, make predictions and the ability of a machine to operate over data without having to give static program instructions to it. Machine Learning is the field of computer science that gives machines/computers the ability to learn without being explicitly programmed. It is employed in a range of computing tasks where designing & programming explicit algorithms with great performance is infeasible, this includes email filtering, intruder detection in networks, computer vision, optical character recognition (OCR), etc. | |
Machine learning is considered to be closely related to computational statistics which as we know focuses on prediction-making through the use of computers. It is also conflated with Data mining because of the exploratory data analysis involved in b |
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/bin/bash | |
################################################################################## | |
# ---------------------------------------------------------------- | |
# THIS SCRIPT WILL HELP YOUR AUTOMATE THE DOCKER INSTALATION STEPS | |
# ---------------------------------------------------------------- | |
# Test was run via aws ec2 instance. | |
# | |
# AUTHOR: | |
# Name: Allie Silver Ubisse |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/bin/bash | |
################################################################################## | |
# ---------------------------------------------------------------- | |
# THIS SCRIPT WILL HELP YOUR AUTOMATE THE DOCKER INSTALATION STEPS | |
# ---------------------------------------------------------------- | |
# Test was run via aws ec2 instance. | |
# | |
# AUTHOR: | |
# Name: Allie Silver Ubisse |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/bin/bash | |
################################################################################## | |
# ---------------------------------------------------------------- | |
# THIS SCRIPT WILL HELP YOUR AUTOMATE THE DOCKER INSTALATION STEPS | |
# ---------------------------------------------------------------- | |
# Test was ran on aws ec2 instance. | |
# | |
# AUTHOR: |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# A simple cheat sheet of Spark Dataframe syntax | |
# Current for Spark 1.6.1 | |
# import statements | |
from pyspark.sql import SQLContext | |
from pyspark.sql.types import * | |
from pyspark.sql.functions import * | |
#creating dataframes | |
df = sqlContext.createDataFrame([(1, 4), (2, 5), (3, 6)], ["A", "B"]) # from manual data |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/bin/bash | |
######################################################################################## | |
# START, STOP or STATUS # | |
# ---------------------------- # | |
# This scrip is intended to help you start, stop or get the IP address of # | |
# Current running EC2. # | |
# This will require you to 1st configure your AWC-CLI, namualy to ensure safety # | |
# # | |
# Please read the code to ensure that It does not cause any security issues # | |
# # |
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.