Building AI Projects Machine Learning & Deep Learning
Building AI Projects Machine Learning & Deep Learning, available at $19.99, has an average rating of 4.83, with 12 lectures, based on 3 reviews, and has 1514 subscribers.
You will learn about Learn the concepts of Python,Machine learning, Deep Learning,Time series. Implement Real World Projects with Proof Of Concept This course consists of 25+ hours video content and Downloadable files for all videos Data Scientists need to have a solid grasp of ML 5 Different Practical Data Science projects with I python Notebooks This course is ideal for individuals who are Beginner into Machine Learning or Beginner into Python or Fresher to get job into Machine Learning Engineer or Career transition from Non Technical into Data Science It is particularly useful for Beginner into Machine Learning or Beginner into Python or Fresher to get job into Machine Learning Engineer or Career transition from Non Technical into Data Science.
Enroll now: Building AI Projects Machine Learning & Deep Learning
Summary
Title: Building AI Projects Machine Learning & Deep Learning
Price: $19.99
Average Rating: 4.83
Number of Lectures: 12
Number of Published Lectures: 12
Number of Curriculum Items: 12
Number of Published Curriculum Objects: 12
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn the concepts of Python,Machine learning, Deep Learning,Time series. Implement Real World Projects with Proof Of Concept
- This course consists of 25+ hours video content and Downloadable files for all videos
- Data Scientists need to have a solid grasp of ML
- 5 Different Practical Data Science projects with I python Notebooks
Who Should Attend
- Beginner into Machine Learning
- Beginner into Python
- Fresher to get job into Machine Learning Engineer
- Career transition from Non Technical into Data Science
Target Audiences
- Beginner into Machine Learning
- Beginner into Python
- Fresher to get job into Machine Learning Engineer
- Career transition from Non Technical into Data Science
Course Description:
Are you ready to dive into the world of Artificial Intelligence and develop practical skills in Machine Learning and Deep Learning? This comprehensive course is designed to take you on an exciting journey through the realms of AI, enabling you to create real-world projects from scratch.
In this hands-on course, you’ll embark on a dynamic learning experience where you’ll build and deploy a series of Machine Learning and Deep Learning projects, starting from the very basics and progressing to advanced applications. Whether you’re a beginner looking to get started in AI or an experienced practitioner aiming to expand your project portfolio, this course caters to all levels of expertise.
Key Highlights:
– Project-Centric Learning: This course revolves around project-based learning. You won’t just study theory; you’ll apply your knowledge to solve practical problems. Each module introduces a new project, ensuring you gain practical experience.
– From Fundamentals to Mastery: We begin with the fundamentals, ensuring that even beginners can grasp the concepts. As the course progresses, we delve into advanced topics, equipping you with the skills needed to tackle complex AI challenges.
– Wide Range of Applications: You’ll explore a diverse range of applications, including image classification, natural language processing, recommendation systems, and more. These projects mirror real-world scenarios, providing valuable insights into AI’s versatility.
– Deep Dive into Deep Learning: Deep Learning is a core component of modern AI. You’ll work with neural networks, convolutional networks, and recurrent networks, and explore cutting-edge techniques to tackle complex tasks.
– Deployment and Scaling: It’s not enough to build models; you’ll also learn how to deploy them, making your projects accessible to a wider audience. You’ll explore cloud-based solutions and scaling strategies.
– Collaborative Environment: Engage with fellow learners in a collaborative environment. Share your insights, seek assistance, and collaborate on group projects, mimicking the collaborative nature of AI development in the real world.
– Mentorship and Support: Experienced AI practitioners and instructors will guide you throughout the course. You’ll receive expert insights and feedback to help you refine your projects.
Upon completion of this course, you’ll emerge with a robust AI portfolio, showcasing your ability to create intelligent solutions from the ground up. Whether you aspire to work in AI research, and data science, or simply want to harness the power of AI for your projects, this course equips you with the skills and confidence to succeed in the world of Machine Learning and Deep Learning. Join us on this exciting journey into the realm of AI, and let’s build the future together, one project at a time!
Course Curriculum
Chapter 1: Project_1 – Flight_Fare_Prediction
Lecture 1: Introduction to Problem Definition and EDA
Lecture 2: Feature Engineering and Applying Classical ML Models
Lecture 3: Deploy the Model with Flask Framework
Chapter 2: Project_2_Mushroom Classification
Lecture 1: Introduction to Classification and Exploratory Data Analysis
Lecture 2: Building The Benchmark Model and Evaluation
Chapter 3: Project_3_NurserySchool_Application_Classification
Lecture 1: Introduction to NurserySchool and EDA
Lecture 2: Logistic Regression, SVM, Decision Tree Models & Evaluation metrics
Chapter 4: Project_4_Toxic_Comments_Classification
Lecture 1: Introduction to Toxic Comments and EDA
Lecture 2: NLP – Tokenized Sequences for Visualization
Lecture 3: Model Refinement – Optimize NB,SVM,LR with Feature Weight
Chapter 5: Project_5_UK_Road_Accident_Timeseries_Forecasting
Lecture 1: Introduction to UK Road Accidents and EDA
Lecture 2: Forecast UK Accident rates based on Number of Casualties on SARIMA,FbP,LSTM's
Instructors
-
Akhil Vydyula
Data Scientist | Data & Analytics Specialist | Entrepreneur
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 0 votes
- 3 stars: 0 votes
- 4 stars: 1 votes
- 5 stars: 2 votes
Frequently Asked Questions
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