The Complete Machine Learning Lifecycle: A Step-by-Step Guide for 2025
Why it matters: A step-by-step guide to the machine learning lifecycle in 2025, covering key phases and best practices.
Sanksshep Mahendra
Sanksshep Mahendra is a technology executive with success in driving, vision, strategy, design, and execution of software engineering for the web, mobile, apps, social, voice, IoT, applications along with Machine learning and AI. His expertise lies in partnering with business leaders, powering through roadblocks, and leading global teams to deliver disruptive products that advance the organization’s mission and capture game-changing results in the market. Sanksshep Mahendra has a lot of experience in M&A and compliance, he holds a Master's degree from Pratt Institute and executive education from Massachusetts Institute of Technology, in AI, Robotics, and Automation.
Future trends in AI business applications
Why it matters: Future Trends in AI Business Applications: Discover AI’s impact on personalized experiences, automation, and insights.
Building an AI-Driven Business: Strategies and Challenges
Why it matters: Building an AI-driven business: strategies for innovation, managing risks, defining AI opportunities, and scaling success.
Challenges AI faces today
Why it matters: Challenges AI faces today include technical, ethical, and social issues across development, data, bias, and regulation.
Introduction to computer vision
Why it matters: Introduction to Computer Vision: Learn image recognition, AI object detection, and applications in healthcare, vehicles.
Common algorithms in AI: supervised, unsupervised, and reinforcement learning
Why it matters: Explore common AI algorithms like supervised, unsupervised, and reinforcement learning, their applications, and challenges.
Basics of neural networks and how they work
Why it matters: Basics of neural networks, their structure, processing, training, types, applications, and future developments.
AI in mobile applications
Why it matters: Learn how AI is revolutionizing mobile apps, enhancing areas like health, gaming, shopping, and mobile security.
How AI learns: datasets and data processing
Why it matters: How AI learns through datasets and data processing: exploring data types, methodologies, and future trends in AI.
Key skills to get started with AI
Why it matters: Learn the key skills for AI development, including programming, machine learning, and essential math concepts.