4.12 (730 reviews)
☑ Machine Learning and its applications
☑ Building End to End Machine Learning Projects
☑ Deployment of Machine & Deep learning algorithms
Do you feel overwhelmed going through all the AI and Machine learning study materials?
These Machine learning and AI projects 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!!
Project 1 - AI Project Web application for Object Identification
Project Requirements & Django Project Creation
Backend creation using pretrained Keras model - Resnet50
Adding Form to django App & uploading image
Integrating web application with deep learning backend
Project 2 - Deep Learning Project : Dog Breed Prediction (Kaggle dataset)
Dog Breed Prediction
AI Project : End to End Credit Card Fraud Detection
AI Project : Fraud Detection -Introduction
Module 1 : Agenda
Module 1 : Understanding Objective
Module 1: Kafka for gathering live credit card data
Module 1 : Cassandra for storing data
Module 1: Solution System Design
Module 2: Agenda
Module 2: System Requirements
Module 2: Java Installation
Module 2: Kafka Installation
Module 2: Anaconda Installation
Module 2: Docker Installation
Module 2: Cassandra Installation
Module 3: Agenda
Module 3: Loading & Preprocessing of Data
Module 3 : Sampling Techniques
Module 3: Estimators to be considered
Module 3: Connecting transformers & estimators using Pipeline
Module 4: Agenda
Module 4: Code Flow
Module 4: Class to connect Cassandra
Module 4: Class code for Model Config & Training
Module 4: Hyperparameter Tuning
Module 4: Stitching all components
Module 5: Agenda
Module 5: Model Persistence & Selection
Module 5: Revisiting Solution
Module 5 : Model behind Kafka Consumer
Module 5: Model behind REST using Flask
The projects are bit nice, But the main problem is they have not shared the source code which makes difficult to refer and learn
Its good but need to explain basic introduction of tools which are going to use while real time project is doing. And please do mention about the preinstallations links before starting this course as to search for pip installed tools like tensor flow,keras... some people dont get those after searching to make them installed. I suggest to please include those links to install prerequisite installation tools to help students who dont have prior knowledge in these and inorder to save time as well
really crisp and to the point explanation... Best part is he doesn't even waste time introducing himself... Plus he definitely has experience in what he's teaching so guess he is only trying to create more value from his knowledge by sharing...
The instructor has not provided the downloadable resources of source code so that we can implement is correctly and have a better understanding.
The teacher thinks we know everything he teaches. Also, I haven't seen any asnwer to the students questions
It was great experience to learn about the "Object Identification" project. But , if you have told that how to install all requirements atleast in short then it would be great. Thank you!
Everything was OKAY, But The instructor should at least know that no matter what project we do, we should maintain a `requirements.txt` so that learners do not have problems while installing dependencies. I wasted my hours trying to figure out which version best suits without producing an error.
There are no exercises that are taught in the videos, looks like they picked up videos from another course and mashed it together
Unfortunately he is using an older version of Django, which is outdated. Even after changing some code, there are still some errors, thus there is not output to be seen.
What was that interface where you were doing this backend test. atleast first give a brief info about the environment thats present on the screen
It was great and an honour for me to enroll a course online from udemy during the pendemic.Thanks to the udemy for providing such useful courses online for all students out there.cheers!