awesomeloveandhiphopfan-blog

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Pet GPS Tracker for Dogs,No Monthly fee, Real-Time Tracking Device App controll(Only for Dog)

#discount #offer #OFF 55% , #Coupons Code: 2PJOUAJ9 (Fit for All Size) For #amazon #items #deal Jk #Smart #Light #Bulb Compatible with Alexa #WiFi Light Bulbs #Color Changing A19 Soft White Dimmable E27 No Hub Require 7 W 80 Watt Equivalent 800 Lumen #couponcode http://www.amazon.com/dp/B07V3R7H8L?ref=myi_title

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Pet GPS Tracker for Dogs,No Monthly fee, Real-Time Tracking Device App controll(Only for Dog)

REAL-TIME TRACKING,NO MONTHLY FEE:Petfon GPS tracker combines GPS, WiFi, bluetooth, and long distance wireless technologies for accurate real-time positioning. The small, durable, and rainproof device allows you to track your pet's activity and pinpoint his/her location in real time. Petfon GPS tracker is free of any service fee or monthly fee.

🐕EASY TO USE,LONG DISTANCE TRACKING: Petfon GPS Tracker is easy to install and use. With the app, you can view your pet's activities and pinpoint his location at any time. The capable of tracking ranges up to 0.65 miles in downtown/dense space and 3.5 miles in an open environment.But if you are using it in areas with dense forests or similar environments,the tracking distance could be decreased.

🐕GEOFENCING,MULTICOLOR ALERT,CUSTOMIZABLE VOICE COMMAND: With Petfon GPS tracker you can define a safe area around your pet's location and get notified instantly if your pet leaves that area. You can also activate the colorful lights on the GPS tracker to locate your pet more easily in dim light or at night time. Voice commands can be recorded and stored on the tracker to communicate with your pets remotely.The speaker on Petfon Tracker emits up to 70 decibels of sound.

🐕RAINPROOF,LONG STANDBY TIME: The Petfon GPS tracker is small and durable (42mm*42mm*18mm, weight: 27.6g). The rainproof feature enables it to work in wet weather but do not working for swimming. Petfon GPS Tracker's battery can last up to 8-16 hours and comes with a compact charging station. It can recharge the device multiple times, which is perfect for going off the grid

🐕NOTE: The Petfon GPS Tracker is optimized to let you track your pet during walks - it is not designed for indoor tracking or remote monitoring. Tracking may not be accurate in these conditions (like all uses of GPS).Please don't try to track your pets when you are inside the house with pets running outside, the performance could not be guaranteed, the connection could be very unstable due to massive obstructions between controller and tracker.

#discount #offer #OFF 55% , #Coupons Code: 2PJOUAJ9 (Fit for All Size) For #amazon #items #deal Jk #Smart #Light #Bulb Compatible with Alexa #WiFi Light Bulbs #Color Changing A19 Soft White Dimmable E27 No Hub Require 7 W 80 Watt Equivalent 800 Lumen #couponcode http://www.amazon.com/dp/B07V3R7H8L?ref=myi_title

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Core Spatial Data Analysis: Introductory GIS with R and QGIS

MASTER SPATIAL DATA ANALYSIS IN R & QGIS: HANDS ON TRAINING WITH A REAL SPATIAL DATA PROJECT!

Do you find GIS & Spatial Data books & manuals too vague, expensive & not practical and looking for a course that takes you by hand, teaches you all the concepts, and get you started on a real life project?

Or perhaps you want to save time and learn how to automate some of the most common GIS tasks?

I'm very excited you found my spatial data analysis course. My course provides a foundation to carry out PRACTICAL, real-life spatial data analysis tasks in popular and FREE software frameworks.

My name is MINERVA SINGH and i am an Oxford University MPhil (Geography and Environment) graduate. I am currently pursuing a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life spatial data from different sources and producing publications for international peer reviewed journals.

In this course, actual spatial data from the Tam Dao National Park in Vietnam will be used to give a practical hands-on experience of working with real life spatial data and understanding what kind of questions spatial data can help us answer. The underlying motivation for the course is to ensure you can put spatial data analysis into practice today. Start analyzing spatial data for your own projects, whatever your skill level and IMPRESS your potential employers with an actual example of your spatial data analysis abilities.

This is a core course in spatial data analysis, i.e. we will focus on learning the most important and widely encountered spatial data analysis tasks in both R and QGIS

It is a practical, hands-on course, i.e. we will spend a tiny amount of time dealing with some of the theoretical concepts related to spatial data analysis. However, majority of the course will focus on working with the spatial data from the Tam Dao National Park, Vietnam. After each video you will learn a new concept or technique which you may apply to your own projects.

TAKE ACTION TODAY! I will personally support you and ensure your experience with this course is a success.

Who this course is for:

Academics

Researchers

Conservation managers

Anybody who works/will work with spatial data.

#Core #Spatial #Data #Analysis: Introductory GIS with R and QGIS 93% off #couponcode for #udemy #course https://www.udemy.com/core-spatial-data-analysis-with-r-and-qgis/?couponCode=EARLYBIRD_COREGIS

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[Intermediate] Spatial Data Analysis with R, QGIS & More

PRACTICAL TRAINING WITH REAL SPATIAL DATA FROM DIFFERENT SOURCES.

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DEVELOP MAD GIS SKILLS AND PERFORM SPATIAL DATA ANALYSIS USING FREE KICKASS TOOLS SUCH AS QGIS, R, GRASS AND GOOGLE EARTH.

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This course is designed to take users who use R and QGIS for basic spatial data/GIS analysis to perform more advanced GIS tasks (including automated workflows and geo-referencing) using a variety of different data. In addition to making you proficient in R and QGIS for spatial data analysis, you will be introduced to another powerful free GIS software.. GRASS.

This course takes a completely practical approach to spatial data analysis and mapping- Each lecture will teach you a practical application/processing technique which you can apply easily.

The course is taught by Minerva Singh, A PhD graduate from Cambridge University, UK, who has several years of research experience in Quantitative Ecology and an MPhil in Geography and Environment from Oxford University. Minerva has published papers in international peer reviewed journals and given talks at international conferences.  

The underlying motivation for the course is to ensure you can put spatial data analysis into practice today and develop sound GIS analysis skills. You’ll be able to start analyzing spatial data for your own projects, and IMPRESS YOUR FUTURE EMPLOYERS with examples of your PRACTICAL spatial data analysis abilities. This course is different from other training resources. Each lecture seeks to enhance your GIS skills in a demonstrable and tangible manner and provide you with practically implementable GIS solutions.

This is an intermediate course in spatial data analysis, i.e. we will build on on basic spatial data analysis tasks (such as those covered in the beginner version course: Core Spatial Data Analysis: Introductory GIS with R and QGIS) and teach users how to practically implement more complex GIS tasks such as interpolation, mapping spatial data, geo-referencing and detailed vector processing. Additionally you will be introduced to preliminary geo-statistics and mapping/visualizing spatial data.

This course covers complex GIS techniques, and by completing this course, you will be implementing these PRACTICALLY in freely-available software, thus making you MORE ATTRACTIVE TO EMPLOYERS.  

It is a practical, hands-on course, i.e. we will spend a tiny amount of time dealing with some of the theoretical concepts pertaining to the different spatial data analysis techniques demonstrated in the course. However, majority of the course will focus on working with real spatial data from different sources. After each video you will learn how to practically implement a new concept or technique in the different softwares used for the course.

During the course of my research I have discovered that R is a powerful tool for collating and analyzing spatial data acquired from different sources.  Proficiency in spatial data analysis in R and QGIS has helped me publish more peer reviewed papers faster. Feel free to check out my profile on ResearchGate.

FREE BONUS: You will have access to all the data used in the course, along with the R code files. You will also have access to future lectures, resources and R code files. Enroll in the course today & take advantage of this special bonus!

I don’t have to remind you that we have a RISK-FREE GUARANTEE in the case of you not being satisfied with the course. Take action now!

Who this course is for:

People who have a basic understanding of spatial data analysis and want to learn more

Students interested in building up on skills acquired through my previous course Core Spatial Data Analysis: Introductory GIS with R and QGIS

Academics

Conservation managers

GIS Technicians.

[Intermediate] #Spatial #Data #Analysis with R, QGIS & More 92% off #coupon for #udemy #course https://www.udemy.com/intermediate-spatial-data-analysis-with-r-qgis-more/?couponCode=INTERMEDIATE_FREE123

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Spatial Data Analysis With ArcGIS Desktop: Master GIS Techniques and Open Doors to Amazing Geospatial Careers

I WANNA LEARN SPATIAL DATA ANALYSIS, BUT…

I found most spatial data books & manuals vague

There are no courses that actually teach me how it’s actually done

Available resources are expensive & I can’t afford them

I want to get a job in the field of GIS and geospatial analysis

I work in the field of ecology or quantitative social sciences or hydrology or civil engineering or geography

If you found yourself in one of these situations, then..

I’VE GOT GREAT NEWS FOR YOU!

Over the past few months, I have published multiple courses on Udemy around this topic which will be tremendously helpful to you & most important of all AFFORDABLE!

Today, I’ve created yet another powerful resource for you!

In this course, over 50+ hands-on and practical lecture, I will help you master the most common and important geo-processing tasks that can be performed with ArcGIS Desktop, one of THE MOST important GIS software tools available.

I will also show you the kind of questions answered through Spatial Analysis & data used.

THE STEPS I’LL WALK YOU THROUGH:

First of all, we’ll start some basic GIS tasks like “Zooming”.

Then, we’ll move into more complex processing tasks like “Geo-Statistics”.

We’ll also deal with some theoretical concepts related to Spatial Data Analysis, and then we’ll focus on implementing some of the most common GIS techniques (all the way showing you how to execute these tasks in ArcGIS Desktop).

The stuff you’ll learn from this course will be extremely useful in terms of you being able to implement it on future Spatial Data projects you’ll be working on (in a variety of disciplines from ecology to engineering).

LEARN FROM AN ACTUAL EXPERT IN THIS AREA:

My name is MINERVA SINGH.

I am an Oxford University MPhil (Geography and Environment) graduate.

I recently finished my PhD at Cambridge University (Tropical Ecology and Conservation).

I have SEVERAL YEARS OF EXPERIENCE in analyzing REAL LIFE DATA from different sources in ArcGIS Desktop.

I’ve also published my work in many international peer reviewed journals.

HERE IS HOW MY COURSE IS UNIQUE..

My course is a HANDS ON TRAINING with REAL data.

It’s a step by step course covering both the THEORY & APPLICATION of Spatial Data Analysis.

I teach Practical Stuff that you can learn quickly and start implementing NOW.

This is one of the most comprehensive courses on this topic.

I advise you to take advantage of it & enroll in the course TODAY!

TAKE ACTION TODAY! I will personally support you and ensure your experience with this course is a success. I answer all questions put to me and guide my students when they get stuck.

Please make sure you have access to ArcGIS before enrolling

Who this course is for:

Academics and Researchers

Conservation managers, field ecologists and social scientists

People looking to get started in the field of GIS Analysis

Students of Geography, Environmental Sciences, Geology, Hydrology, Engineering, Earth Sciences and Ecology

People looking to use ArcGIS Desktop in academic or professional settings.

90% off #udemy #course #ArcGIS #Desktop For #Spatial #Analysis: Go From Basic To Pro!! #couponcode HERE! https://www.udemy.com/arcgis-desktop-for-spatial-analysis-go-from-basic-to-pro/?couponCode=ARCGIS_PROMO_20

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Satellite Remote Sensing Data Bootcamp With Opensource Tools

ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT BASIC SATELLITE REMOTE SENSING.

Are you currently enrolled in either of my Core or Intermediate Spatial Data Analysis Courses?

Or perhaps you have prior experience in GIS or tools like R and QGIS?

You don't want to spend 100s and 1000s of dollars on buying commercial software for imagery analysis?

The next step for you is to gain profIciency in satellite remote sensing data analysis.

MY COURSE IS A HANDS ON TRAINING WITH REAL REMOTE SENSING DATA WITH OPEN SOURCE TOOLS!

My course provides a foundation to carry out PRACTICAL, real-life remote sensing analysis tasks in popular and FREE software frameworks with REAL spatial data. By taking this course, you are taking an important step forward in your GIS journey to become an expert in geospatial analysis.

Why Should You Take My Course?

I am an Oxford University MPhil (Geography and Environment) graduate. I also completed a PhD at Cambridge University (Tropical Ecology and Conservation).

I have several years of experience in analyzing real life spatial remote sensing data from different sources and producing publications for international peer reviewed journals.

In this course, actual satellite remote sensing data such as Landsat from USGS and radar data from JAXA  will be used to give a practical hands-on experience of working with remote sensing and understanding what kind of questions remote  sensing can help us answer.

This course will ensure you learn & put remote sensing data analysis into practice today and increase your proficiency in geospatial analysis.

Remote sensing software tools are very expensive and their cost can run into thousands of dollars. Instead of shelling out so much money or procuring pirated copies (which puts you at a risk of prosecution), you will learn to carry out some of the most important and common remote sensing analysis tasks using a number of popular, open source GIS tools such as R, QGIS, GRASS and ESA-SNAP.  All of which are in great demand in the geospatial sector and improving your skills in these is a plus for you.

This is an introductory course, i.e. we will focus on learning the most important and widely encountered remote sensing data processing and analyzing tasks in R, QGIS, GRASS and ESA-SNAP

You will also learn about the different sources of remote sensing data there are and how to obtain these FREE OF CHARGE and process them using FREE SOFTWARE.

In addition to all the above, you’ll have MY CONTINUOUS SUPPORT to make sure you get the most value out of your investment!

ENROLL NOW :)

Who this course is for:

People with prior expereince of working spatial data

GIS analysts

Ecologists

Forestry and Conservation Practioners

Geographers

Geologists

92% off #udemy course #couponcode #Satellite #Remote Sensing Data #Bootcamp With #Opensource Tools https://www.udemy.com/satellite-remote-sensing-data-bootcamp-with-opensource-tools/?couponCode=REMOTESENSING_15

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Harness The Power Of Machine Learning For Unsupervised & Supervised Learning In Python

HERE IS WHY YOU SHOULD TAKE THIS COURSE:

This course your complete guide to both supervised & unsupervised learning using Python. This means, this course covers all the main aspects of practical data science and if you take this course, you can do away with taking other courses or buying books on Python based data science.

In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal..

By becoming proficient in unsupervised & supervised learning in Python, you can give your company a competitive edge and boost your career to the next level.

LEARN FROM AN EXPERT DATA SCIENTIST WITH +5 YEARS OF EXPERIENCE:

My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I also just recently finished a PhD at Cambridge University.

I have several years of experience in analyzing real life data from different sources  using data science techniques and producing publications for international peer reviewed journals.

Over the course of my research I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic .

This course will give you a robust grounding in the main aspects of machine learning- clustering & classification.

Unlike other Python instructors, I dig deep into the machine learning features of Python and gives you a one-of-a-kind grounding in Python Data Science!

You will go all the way from carrying out data reading & cleaning  to machine learning to finally implementing simple deep learning based models using Python

THE COURSE COMPOSES OF 7 SECTIONS TO HELP YOU MASTER PYTHON MACHINE LEARNING:

• A full introduction to Python Data Science and powerful Python driven framework for data science, Anaconda • Getting started with Jupyter notebooks for implementing data science techniques in Python  • Data Structures and Reading in Pandas, including CSV, Excel and HTML data • How to Pre-Process and “Wrangle” your Python data by removing NAs/No data, handling conditional data, grouping by attributes, etc.

• Machine Learning, Supervised Learning, Unsupervised Learning in Python

• Artificial neural networks (ANN) and Deep Learning. You’ll even discover how to use artificial neural networks and deep learning structures for classification!

With such a rigorous grounding in so many topics, you will be an unbeatable data scientist by the end of the course.

NO PRIOR PYTHON OR STATISTICS OR MACHINE LEARNING KNOWLEDGE IS REQUIRED:

You’ll start by absorbing the most valuable Python Data Science basics and techniques.

I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in Python.

My course will help you implement the methods using real data obtained from different sources.

After taking this course, you’ll easily use packages like Numpy, Pandas, and Matplotlib to work with real data in Python..

You’ll even understand concepts like unsupervised learning, dimension reduction and supervised learning.. I will even introduce you to deep learning and neural networks using the powerful H2o framework!

Most importantly, you will learn to implement these techniques practically using Python. You will have access to all the data and scripts used in this course. Remember, I am always around to support my students!

JOIN MY COURSE NOW!

Who this course is for:

Students Interested In Getting Started With Data Science Applications In The Python Environment

People Wanting To Master The Anaconda iPython Environment For Data Science & Scientific Computations

Students Wishing To Learn The Implementation Of Unsupervised Learning On Real Data Using Python

Students Wishing To Learn The Implementation Of Supervised Learning (Classification) On Real Data Using Python

Students Looking To Get Started With Artificial Neural Networks & Deep Learning.

92% discount #coupon #udemy #course for #Clustering & #Classification With #Machine Learning In #Python #couponcode https://www.udemy.com/clustering-classification-with-machine-learning-in-python/

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Learn 16 Machine Learning Algorithms in a Fun and Easy along with Practical Python Labs using Keras

Welcome to the Fun and Easy Machine learning Course in Python and Keras.  

Are you Intrigued by the field of Machine Learning? Then this course is for you! We will take you on an adventure into the amazing of field Machine Learning. Each section consists of fun and intriguing white board explanations with regards to important concepts in Machine learning as well as practical python labs which you will enhance your comprehension of this vast yet lucrative sub-field of Data Science.

So Many Machine Learning Courses Out There, Why This One?

This is a valid question and the answer is simple. This is the ONLY course on Udemy which will get you implementing some of the most common machine learning algorithms on real data in Python. Plus, you will gain exposure to neural networks (using the H2o framework) and some of the most common deep learning algorithms with the Keras package.

We designed this course for anyone who wants to learn the state of the art in Machine learning in a simple and fun way without learning complex math or boring explanations.  Each theoretically lecture is uniquely designed using whiteboard animations which can maximize engagement in the lectures and improves knowledge retention. This ensures that you absorb more content than you would traditionally would watching other theoretical videos and or books on this subject.

What you will Learn in this Course

This is how the course is structured:

Regression – Linear Regression, Decision Trees, Random Forest Regression,

Classification – Logistic Regression, K Nearest Neighbors (KNN), Support Vector Machine (SVM) and Naive Bayes,

Clustering - K-Means, Hierarchical Clustering,

Association Rule Learning - Apriori, Eclat,

Dimensionality Reduction - Principle Component Analysis, Linear Discriminant  Analysis,

Neural Networks - Artificial Neural Networks, Convolution Neural Networks, Recurrent Neural Networks.

Practical Lab Structure You DO NOT need any prior Python or Statistics/Machine Learning Knowledge to get Started. The course will start by introducing students to one of the most fundamental statistical data analysis models and its practical implementation in Python- ordinary least squares (OLS) regression. Subsequently some of the most common machine learning regression and classification techniques such as random forests, decision trees and linear discriminant analysis will be covered. In addition to providing a theoretical foundation for these, hands-on practical labs will demonstrate how to implement these in Python. Students will also be introduced to the practical applications of common data mining techniques in Python and gain proficiency in using a powerful Python based framework for machine learning which is Anaconda (Python Distribution). Finally you will get a solid grounding in both Artificial Neural Networks (ANN) and the Keras package for implementing deep learning algorithms such as the Convolution Neural Network (CNN). Deep Learning is an in-demand topic and a knowledge of this will make you more attractive to employers.

Excited Yet?

So as you can see you are going to be learning to build a lot of impressive Machine Learning apps in this 3 hour course. The underlying motivation for the course is to ensure you can apply Python based data science on real data into practice today. Start analyzing  data for your own projects, whatever your skill level and IMPRESS your potential employers with an actual examples of your  machine learning abilities.

It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to data science. However, majority of the course will focus on implementing different  techniques on real data and interpret the results. After each video you will learn a new concept or technique which you may apply to your own projects.

TAKE ACTION TODAY! We will personally support you and ensure your experience with this course is a success. And for any reason you are unhappy with this course, Udemy has a 30 day Money Back Refund Policy, So no questions asked, no quibble and no Risk to you. You got nothing to lose. Click that enroll button and we'll see you in side the course.

Who this course is for:

Student who starting out or interested in Machine Learning or Deep Learning.

Students with Prior Python Programming Exposure Who Want to Use it for Machine Learning

Students interested in gaining exposure to the Keras library for Deep Learning.

Data analysts who want to expand into Machine Learning.

College students who want to start a career in Data Science.

92% discount #coupon #udemy #course for The Fun and Easy Guide to #Machine #Learning using #Keras #couponcode https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/

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Complete Deep Learning In R With Keras & Others

YOUR COMPLETE GUIDE TO ARTIFICIAL NEURAL NETWORKS & DEEP LEARNING IN R:      

This course covers the main aspects of neural networks and deep learning. If you take this course, you can do away with taking other courses or buying books on R based data science.

In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in neural networks and deep learning in R, you can give your company a competitive edge and boost your career to the next level!

LEARN FROM AN EXPERT DATA SCIENTIST:

My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University.

I have +5 years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals.

Over the course of my research I realized almost all the R data science courses and books out there do not account for the multidimensional nature of the topic .

This course will give you a robust grounding in the main aspects of practical neural networks and deep learning.

Unlike other R instructors, I dig deep into the data science features of R and give you a one-of-a-kind grounding in data science...

You will go all the way from carrying out data reading & cleaning  to to finally implementing powerful neural networks and deep learning algorithms and evaluating their performance using R.

Among other things:

You will be introduced to powerful R-based deep learning packages such as h2o and MXNET.

You will be introduced to deep neural networks (DNN), convolution neural networks (CNN) and unsupervised methods.

You will learn how to implement convolutional neural networks (CNN)s on imagery data using the Keras framework

You will learn to apply these frameworks to real life data including credit card fraud data, tumor data, images among others for classification and regression applications.  

With this course, you’ll have the keys to the entire R Neural Networks and Deep Learning Kingdom!

NO PRIOR R OR STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED:

You’ll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R.

My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real-life.

After taking this course, you’ll easily use data science packages like caret, h2o, mxnet, keras to implement novel deep learning techniques in R. You will get your hands dirty with real life data, including real-life imagery data which you will learn to pre-process and model

You’ll even understand the underlying concepts to understand what algorithms and methods are best suited for your data.

We will also work with real data and you will have access to all the code and data used in the course.

JOIN MY COURSE NOW!

Who this course is for:

People Wanting To Master The R & R Studio Environment For Data Science

Anyone With Prior Exposure To Common Machine Learning Concepts Such As Supervised Learning

Students Wishing To Learn The Implementation Of Neural Networks On Real Data In R

Students Wishing To Learn The Implementation Of Basic Deep Learning Concepts In R.

92% discount #coupon #udemy #course for Complete #Deep #Learning In R With Keras & Others #couponcode https://www.udemy.com/complete-deep-learning-in-r-with-keras-others/