Learn Machine learning & AI [Beginner to advanced content]
Learn Machine learning & AI [Beginner to advanced content], available at $34.99, has an average rating of 4.1, with 34 lectures, based on 1209 reviews, and has 270973 subscribers.
You will learn about Machine Learning and its applications Building End to End Machine Learning Projects Deployment of Machine & Deep learning algorithms This course is ideal for individuals who are Python developers looking for a future in machine learning and Artificial Intelligence (AI). or Machine learning learners looking for live projects to learn from. or Python and Machine learning developers looking for hands on projects to work on Artificial Intelligence (AI). It is particularly useful for Python developers looking for a future in machine learning and Artificial Intelligence (AI). or Machine learning learners looking for live projects to learn from. or Python and Machine learning developers looking for hands on projects to work on Artificial Intelligence (AI).
Enroll now: Learn Machine learning & AI [Beginner to advanced content]
Summary
Title: Learn Machine learning & AI [Beginner to advanced content]
Price: $34.99
Average Rating: 4.1
Number of Lectures: 34
Number of Published Lectures: 34
Number of Curriculum Items: 34
Number of Published Curriculum Objects: 34
Original Price: $44.99
Quality Status: approved
Status: Live
What You Will Learn
- Machine Learning and its applications
- Building End to End Machine Learning Projects
- Deployment of Machine & Deep learning algorithms
Who Should Attend
- Python developers looking for a future in machine learning and Artificial Intelligence (AI).
- Machine learning learners looking for live projects to learn from.
- Python and Machine learning developers looking for hands on projects to work on Artificial Intelligence (AI).
Target Audiences
- Python developers looking for a future in machine learning and Artificial Intelligence (AI).
- Machine learning learners looking for live projects to learn from.
- Python and Machine learning developers looking for hands on projects to work on Artificial Intelligence (AI).
Do you feel overwhelmed going through all the AI and Machine learning study materials?
These Machine learning and AIprojects will get you started with the implementation of a few very interesting projects from scratch.
The first one, a Web application for Object Identification will teach you to deploy a simple machine learning application.
The second one, Dog Breed Prediction will help you building & optimizing a model for dog breed prediction among 120 breeds of dogs. This is built using Deep Learning libraries.
Lastly, Credit Card Fraud detection is one of the most commonly used applications in the Finance Industry. We talk about it from development to deployment. Each of these projects will help you to learn practically.
Who’s teaching you in this course?
I am Professional Trainer and consultant for Languages C, C++, Python, Java, Scala, Big Data Technologies – PySpark, Spark using Scala Machine Learning & Deep Learning- sci-kit-learn, TensorFlow, TFLearn, Keras, h2o and delivered at corporates like GE, SCIO Health Analytics, Impetus, IBM Bangalore & Hyderabad, Redbus, Schnider, JP Morgan – Singapore & HongKong, CISCO, Flipkart, MindTree, DataGenic, CTS – Chennai, HappiestMinds, Mphasis, Hexaware, Kabbage. I have shared my knowledge that will guide you to understand the holistic approach towards ML.
Here are a few reasons for you to pursue a career in Machine Learning:
1) Machine learning is a skill of the future – Despite the exponential growth in Machine Learning, the field faces skill shortage. If you can meet the demands of large companies by gaining expertise in Machine Learning, you will have a secure career in a technology that is on the rise.
2) Work on real challenges – Businesses in this digital age face a lot of issues that Machine learning promises to solve. As a Machine Learning Engineer, you will work on real-life challenges and develop solutions that have a deep impact on how businesses and people thrive. Needless to say, a job that allows you to work and solve real-world struggles gives high satisfaction.
3) Learn and grow – Since Machine Learning is on the boom, by entering into the field early on, you can witness trends firsthand and keep on increasing your relevance in the marketplace, thus augmenting your value to your employer.
4) An exponential career graph – All said and done, Machine learning is still in its nascent stage. And as the technology matures and advances, you will have the experience and expertise to follow an upward career graph and approach your ideal employers.
5) Build a lucrative career– The average salary of a Machine Learning engineer is one of the top reasons why Machine Learning seems a lucrative career to a lot of us. Since the industry is on the rise, this figure can be expected to grow further as the years pass by.
6) Side-step into data science – Machine learning skills help you expand avenues in your career. Machine Learning skills can endow you with two hats- the other of a data scientist. Become a hot resource by gaining expertise in both fields simultaneously and embark on an exciting journey filled with challenges, opportunities, and knowledge.
Machine learning is happening right now. So, you want to have an early bird advantage of toying with solutions and technologies that support it. This way, when the time comes, you will find your skills in much higher demand and will be able to secure a career path that’s always on the rise.
Practical Learning !!
Project-based learning has proven to be one of the most effective ways to engage students and provide a practical application for what they’re learning and it provides opportunities for students to collaborate or drive their learning, but it also teaches them skills such as problem-solving and helps to develop additional skills integral to their future, such as critical thinking and time management
By pursuing this course you will able to understand the concept of Machine learning at the next level you will also get to know about Artificial intelligence and that will boost your skill set to be a successful ML engineer.
Enroll now, see you in class!!
Happy learning!
Team Edyoda
Course Curriculum
Chapter 1: Project 1 – AI Project Web application for Object Identification
Lecture 1: Project Requirements & Django Project Creation
Lecture 2: Backend creation using pretrained Keras model – Resnet50
Lecture 3: Adding Form to django App & uploading image
Lecture 4: Integrating web application with deep learning backend
Chapter 2: Project 2 – Deep Learning Project : Dog Breed Prediction (Kaggle dataset)
Lecture 1: Dog Breed Prediction
Chapter 3: AI Project : End to End Credit Card Fraud Detection
Lecture 1: AI Project : Fraud Detection -Introduction
Lecture 2: Module 1 : Agenda
Lecture 3: Module 1 : Understanding Objective
Lecture 4: Module 1: Kafka for gathering live credit card data
Lecture 5: Module 1 : Cassandra for storing data
Lecture 6: Module 1: Solution System Design
Lecture 7: Module 2: Agenda
Lecture 8: Module 2: System Requirements
Lecture 9: Module 2: Java Installation
Lecture 10: Module 2: Kafka Installation
Lecture 11: Module 2: Anaconda Installation
Lecture 12: Module 2: Docker Installation
Lecture 13: Module 2: Cassandra Installation
Lecture 14: Module 3: Agenda
Lecture 15: Module 3: Loading & Preprocessing of Data
Lecture 16: Module 3 : Sampling Techniques
Lecture 17: Module 3: Estimators to be considered
Lecture 18: Module 3: Connecting transformers & estimators using Pipeline
Lecture 19: Module 4: Agenda
Lecture 20: Module 4: Code Flow
Lecture 21: Module 4: Class to connect Cassandra
Lecture 22: Module 4: Class code for Model Config & Training
Lecture 23: Module 4: Hyperparameter Tuning
Lecture 24: Module 4: Stitching all components
Lecture 25: Module 5: Agenda
Lecture 26: Module 5: Model Persistence & Selection
Lecture 27: Module 5: Revisiting Solution
Lecture 28: Module 5 : Model behind Kafka Consumer
Lecture 29: Module 5: Model behind REST using Flask
Instructors
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EdYoda for Business
Join me on www.edyoda.com
Rating Distribution
- 1 stars: 64 votes
- 2 stars: 60 votes
- 3 stars: 177 votes
- 4 stars: 417 votes
- 5 stars: 491 votes
Frequently Asked Questions
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