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Get started with Machine Learning in no time by learning ML Algorithms & implementing it in live projects to solve real world problems
Get started with Machine Learning in no time by learning ML Algorithms & implementing it in live projects to solve real world problems
Get started with Machine Learning in no time by learning ML Algorithms & implementing it in live projects to solve real world problems
410 backers pledged $14,207 to help bring this project to life.

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Learn Real World Machine Learning By Building Projects

$14,207

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Real World Machine Learning By Building 10 Projects

10 Real-World Projects in Machine Learning
10 Real-World Projects in Machine Learning

We are very excited to start work on our new course on Machine Learning. A course where you will learn to implement cutting edge machine learning algorithms to solve real world problems. We have carefully selected the projects which will cover important aspect of Machine learning such as Supervised Learning, Unsupervised learning and Neural network with deep learning. You will start with real world data available publicly to create these Machine Learning's Projects. It will be a course for serious developers but will be fun and engaging. You will learn step by step implementation and can be a professional ML developer after completing this course.

What is Machine Learning?

Types of Machine Learning
Types of Machine Learning

Machine Learning as a career

Machine learning is the top emerging Job vertical among all technology jobs world wide.

 With new avenues of machine learning such as consumer behaviour analysis, marketing and sales forecasting, IT security, fraud detection , finance and office automation there is a big opportunity for trained Machine learning experts. Our course aims to provide expertise which you can directly transfer in your day to day Jobs.

Machine Learning’s Potential To Change The World

Where Machine Learning can be used
Where Machine Learning can be used

Machine Learning offers a slew of different opportunities in multiple sectors including Business, Medicine, Marketing, etc. From credit card fraud detection to offering a more personalized marketing experience, machine learning can not only help but will also change the way we surf the web, drive our cars and maybe even shower.

Machine Learning is currently one of the hottest trends on the market with companies big and small using learning algorithms to offer a more personalised user experience for their customers.

What This Course Offers

Machine Learning comes with a lot of potential and it doesn’t seem to be stopping any time soon. As technology gets smarter and better, so will your algorithms. If you’ve always wanted to help build a more futuristic world, then this is your chance. We have designed the perfect course for helping you get started with machine learning by helping you understand the key algorithms that are used when writing machine learning programs.

This course won’t focus on the theory or the boring aspects of machine learning, but instead you will actually build your own apps. You will learn how to write the codes and then see them in action. Using 5 projects (Now 10 projects) that range from simple to more complex ones, you’ll actually learn how to think like a machine learning expert.

Why This Course?

This course has been designed keeping in mind all types of learners. It includes something for everyone, from newbies to even advanced programmers. The course focuses on helping you actually learn how to code and write the algorithms, instead of simply focusing on the theoretical or the boring aspects of Machine Learning.

The syllabus has been curated by experts and dedicates itself to bringing you the best approach approach to ML. The course has an example-based approach and will help you become more comfortable applying algorithms to real world problems. The course will focus on building 10 projects from scratch that will not only familiarize you with ML algorithms, but also will help you learn exactly how to use them.

Tentative 10 Projects

First 5 New Projects are the additional projects which will be Added to the Course as we reached our First stretch goal.

Project 1 – Markov Models and K-Nearest Neighbor Approaches to Classifying DNA Sequences

Classifying DNA
Classifying DNA

 In this tutorial, we will explore the world of bioinformatics by using Markov models and K-nearest neighbor (KNN) algorithms to classify E. Coli DNA sequences. This project will use a dataset from the UCI Machine Learning Repository that has 106 DNA sequences, with 57 sequential nucleotides (“base-pairs”) each.

Markov Models and K-Nearest Neighbor
Markov Models and K-Nearest Neighbor

Project 2 – Getting Started with Natural Language Processing In Python

Natural Language Processing
Natural Language Processing

Here we will cover the basics of Natural Language Processing (NLP) methodology, including tokenizing words and sentences, part of speech identification and tagging, and phrase chunking. After this project, the student should have the necessary foundation to begin building and deploying machine learning algorithms for natural language processing.

Natural Language Processing (NLP) Methodology
Natural Language Processing (NLP) Methodology

Project 3 – Obtaining Near State-of-the-Art Performance on Object Recognition Tasks Using Deep Learning

Object Recognition
Object Recognition

 Using the CIFAR-10 object recognition dataset as a benchmark, we will implement a recently published deep neural network that can obtain similar results to state-of-the-art networks, despite having less parameters and smaller computational requirements.

Deep Learning
Deep Learning

Project 4 – Image Super Resolution with the SRCNN

Super Resolution
Super Resolution

In this tutorial, we will implement and use a Tensorflow version of the Super Resolution Convolutional Neural Network (SRCNN) to improve the image quality of degraded images.

Super Resolution Convolutional Neural Network (SRCNN)
Super Resolution Convolutional Neural Network (SRCNN)

Project 5 – Natural Language Processing: Text Classification

Text Classification
Text Classification

Building on the foundation developed in the previous project, this tutorial will dive deeper into Natural Language Processing. We will solve a text classification task using multiple classification algorithms, including a Naïve Bayes classifier, SGD classifier, and linear support vector classifier (SVC).

Project 6 – Stock Market Clustering Project

This project will use a K-means clustering algorithm to identify related companies by finding correlations among stock market movements over a given time span. It will use the open source data from the Yahoo Finance Python module. Also, in this project you are going to do a PCA dimensionality reduction to plot the data on a 2D plot. 

K-means clustering algorithm
K-means clustering algorithm

Project 7 – Breast Cancer Detection

Breast Cancer Detection
Breast Cancer Detection

This second project will build a program to help detect breast cancer malignancies by using a support vector machine. You are also going to use the K-nearest neighbour algorithm to compare and contrast performance with the support vector machine.

K-nearest neighbour algorithm
K-nearest neighbour algorithm

Project 8 – Board Game Review

Board Game Review
Board Game Review

This project is actually going to be predicting board game reviews and in this project you are going to predict the average reviews on a board game based on characteristics such as difficulty, length, number of players. This will be accomplished by performing linear regression analysis.

Linear Regression Analysis
Linear Regression Analysis

Project 9 – Credit Card Fraud Detection

In this project, you are going to do a credit card fraud detection and going to focus on anomaly detection by using probability densities.

Anomaly Detection by Using Probability Densities
Anomaly Detection by Using Probability Densities

Project 10 – Diabetes Onset Detection

This final project is going to be a diabetes onset detection with deep learning grid search. In this project, you will fine-tune a deep learning neural network by performing a grid search. The network will be used to detect the onset of diabetes based on patient data.

Deep Learning Neural Network
Deep Learning Neural Network

About the Company - Eduonix Learning Solutions

Eduonix learning Solutions is the premier training and skill development organization which was started with a vision to bring world class training content, pedagogy and best learning practices to everyone's doorsteps . Eduonix aims to identify and provide the best learning and training environment. It identifies industry veterans and content creators around the globe and bring it to the global audience using number of intuitive platforms for easy and affordable access to quality content.

Our Previous Successful Campaigns

Our Previous Successful Campaigns
Our Previous Successful Campaigns

Risks and challenges

We have successfully delivered all our previous 8 projects on time, so we run a very small risk that we might be able to finish the course in the stipulated time. However, with multiple people working on this project day and night, we are confident that we will not pass the deadline.

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    Super Early Bird offer

    Lifetime access to "Projects in Machine Learning" course. (Retail Price would be $99)

    Includes:
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    • Fully Downloadable
    • Source Codes and Resource Files
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    Early Bird offer

    Lifetime access to "Projects in Machine Learning" course. (Retail Price would be $99)

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    Machine Learning Bundle - Early Bird

    Lifetime access to "Projects in Machine Learning" course. (Retail Price would be $99)

    Also includes "Machine Learning For Absolute Beginners" (Retail Price $49)

    Includes:
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    Machine Learning Bundle

    Lifetime access to "Projects in Machine Learning" course. (Retail Price would be $99)

    Also includes "Machine Learning For Absolute Beginners" (Retail Price $49)

    Includes:
    • R Implementation for all the projects (if 20K is crossed)
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    • Lifetime Access
    • Source Codes and Resource Files
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    Absolute Machine Learning Pack-4 Courses

    Learn everything about Machine Learning, in this bundle you can learn what it takes to be a professional Machine Learning Developer.

    Courses Included in this Bundle are:-

    1. Python 3 Programming Course. (Retail Price $49)
    2. Tensorflow Course (Retail Price $49)
    3. Machine Learning For Absolute Beginners (Retail Price $49)
    4. Projects in Machine Learning course. (Retail Price would be $99)

    Includes:
    • Fully Downloadable
    • Lifetime Access
    • Source Codes and Resource Files
    • R Implementation for all the projects (if 20K is crossed)
    • Mathematics for Machine Learning Course (If 30k is crossed)
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  6. Select this reward

    Pledge US$ 60 or more About US$ 60

    Absolute Machine Learning Pack-4 Courses

    Learn everything about Machine Learning, in this bundle you can learn what it takes to be a professional Machine Learning Developer.

    Courses Included in this Bundle are:-

    1. Python 3 Programming Course. (Retail Price $49)
    2. Tensorflow Course (Retail Price $49)
    3. Machine Learning For Absolute Beginners (Retail Price $49)
    4. Projects in Machine Learning course. (Retail Price would be $99)

    Includes:
    • Fully Downloadable
    • Lifetime Access
    • Source Codes and Resource Files
    • R Implementation for all the projects (if 20K is crossed)
    • Mathematics for Machine Learning Course (If 30k is crossed)
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    1 Year Access Pass - Early Bird

    Access All Courses For Full 1 Year (Regular Price $140)

    You can access all current and Future courses for 365 days at Eduonix.tv. We have over 500 courses at present, and publishing 20-25 courses every month. So in a year we will be ready with another 200-300 courses.

    Never Stop Learning

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    Pledge US$ 99 or more About US$ 99

    1 Year Access Pass

    Access All Courses For Full 1 Year (Regular Price $140)

    You can access all current and Future courses for 365 days at Eduonix.tv. We have over 500 courses at present, and publishing 20-25 courses every month. So in a year we will be ready with another 200-300 courses.

    Never Stop Learning

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Funding period

- (30 days)