The Deep Learning Sentinel (June 24)

Colleagues, our goal is to provide Deep Learning professionals with up-to-date and actionable information to advance your career and income growth.

Product Launches & Innovations 

• AI Bias Research (MIT Technology Review)

• Copilot Studio Enhancements & AI Assistant Support (Microsoft AI)

• ChatGPT Enterprise & Team Expansion (OpenAI)

• Hugging Face Accelerate (Hugging Face)

• Project Astra and Gemini 2.5 Advancements (Google Cloud AI)

• V-JEPA 2 Model Launch (Meta AI)
  
  

Featured Articles

• “Deep Learning: A Overview of Theory and Architectures” (IEEE Xplore)

• “Deep learning-based software engineering: progress, challenges, and opportunities” (Springer Nature Link)

• “Introduction to Deep Learning” Geeks for Geeks  (an excellent read for those new to DL)

• “Multimodal deep learning improves recurrence risk prediction in pediatric low-grade gliomas” (Neuro-Oncology)

Featured Resources

• DeepLearningAI https://www.deeplearning.ai/

• Deep Learning - nVidia Developer https://developer.nvidia.com/deep-learning 

• GitHub Deep Learning

• Keras - A superpower for ML developers

Events

• ML Conference Munich - June 25 & 26, 2025 (MLCon Munich)

• CDAO Government - June 25 & 26, 2025 (Chief Data & Analytics Officers Government)

• Arize:Observe - June 25, 2025 (San Francisco, CA)
  Deep Learning for Science School - June 23-27, 2025 (NERSC - Berkeley Lab)

• Radar AI Edition - June 26, 2025 (DataCamp - online)

Career Development - Certs & Training

• Data Structures, Algorithms, and Deep Learning Optimization

• Deep Learning A-Z 2025: Neural Networks, AI & ChatGPT

• Deep Learning Specialization

• Deep Learning with TensorFlow & PyTorch

• Deep Learning with Tensorflow, Keras and PyTorch 

• Deep Learning Specialization

• Deep Learning with PyTorch

• Machine Learning with Python: from Linear Models to Deep Learning

• Neural Networks and Deep Learning

• Structuring Deep Learning Projects

• TensorFlow Developer Professional Certificate

Enroll today (teams & execs are welcome). 

Much success in your DL career journey, Lawrence E. Wilson - AI Academy (share with colleagues & friends)

Machine Learning Engineer - 10 Best Practices, Portals & Career Development

Colleagues, this post will help you accelerate your career and income potential in the Machine Learning domain. Whether you are new to ML or or looking to advance your existing ML career path this post has valuable information for you.

Best Practices

1. Master Fundamentals: Deepen understanding of math, statistics, and core ML algorithms.

2. Hands-on Project Building: Create a robust portfolio of diverse, real-world projects (e.g., on GitHub, Kaggle).

3. Stay Current with Research: Regularly read papers from leading institutions (DeepMind, OpenAI) and platforms (Hugging Face) to understand cutting-edge advancements.

4. Specialize Strategically: Focus on niche areas like NLP (Hugging Face), computer vision, or MLOps, aligning with industry trends.

5. Develop Deployment Skills: Gain proficiency in bringing models to production (MLOps, cloud platforms like Azure AI).

6. Contribute to Open Source: Actively engage in projects on platforms like Hugging Face or GitHub to collaborate and gain visibility.

7. Network Actively: Connect with peers and mentors on platforms like LinkedIn and at conferences to learn and find opportunities.

8. Prioritize Ethical AI: Understand and apply principles of responsible AI, fairness, and interpretability in all projects.

9. Cultivate Business Acumen: Understand how ML solutions solve real-world business problems and communicate technical concepts clearly.

10. Continuous Learning: The field evolves rapidly, so commit to lifelong learning through courses, certifications, and experimentation.

Resource Portals

• Anthropic

• Hugging Face

• GitHub Artificial Intelligence

• Google Deepmind

• MIT Technology Review - Artificial Intelligence

• Meta AI

• Microsoft AI

• OpenAI

• Stanford AI Lab

Specializations, Master Classes and Certifications

• Applied Machine Learning Specialization 

• AWS Certified Machine Learning

• AWS Machine Learning Engineer

• Data Structures, Algorithms, and Machine Learning Optimization

• Linear Algebra for Machine Learning

• Machine Learning / AI Engineer

• Machine Learning: Foundations using R Specialization

• Machine Learning with PyTorch

• Machine Learning Fundamentals with Python and SQL Specialization

• Structuring Machine Learning Projects

• Machine Learning Specialization

• IBM Machine Learning Professional Certificate

• Structuring Machine Learning Projects

• Understanding Machine Learning 

Enroll today (teams & executives are welcome).  

Much success in your career journey, Lawrence E. Wilson - AI Academy (share with your team)

Machine Learning Careers - Interviews, Project Portfolios & Certifications (Your competitive edge)

Colleagues, are you seeking to land the next job in your Machine Learning career journey … either within your current company or with a new employer? All hiring managers need to answer three fundamental questions in the interview process before making a job offer.

Interview Questions

1. Skills: Can you do the job?

2. Motivation: Will you do the job?

3. Fit: Will you be a team player and fit into the company culture?

Professional Portfolio

Creating a high qualityMachine Learning professional portfolio combined with having industry-leading certifications - along with relevant work experience - will put you at the top of the candidate pool when answering the “Skills” question.

What is a Project Portfolio? 

1. A project portfolio is a collection of projects, programs, and operations managed collectively to achieve strategic objectives. 

2. It demonstrates your diverse skills, experience, and proven ability to deliver results, showcasing your value and strategic impact to potential employers or for internal advancement.

What Makes a Project Portfolio Valuable?

1. Strategic Alignment: Connecting projects to organizational goals.

2. Resource Management: Efficient allocation of people and assets.

3. Risk Management: Identifying and mitigating potential threats.

4. Performance Monitoring: Tracking progress and outcomes.

5. Stakeholder Communication: Keeping all parties informed and engaged.

What are the best portals to host your project portfolio?

1. GitHub

2. LinkedIn

3. Behance

4. Dribbble

5. Kaggle

6. Hugging Face

7. Personal Website (WordPress, Wix, Squarespace, Webflow - Offers maximum customization & a professional brand presence)

Industry-Leading Certifications & Training

• Applied Machine Learning Specialization 

• AWS Certified Machine Learning

• AWS Machine Learning Engineer

• Data Structures, Algorithms, and Machine Learning Optimization

• Linear Algebra for Machine Learning

• Machine Learning / AI Engineer

• Machine Learning: Foundations using R Specialization

• Machine Learning Fundamentals with Python and SQL Specialization

• Machine Learning with PyTorch

• Structuring Machine Learning Projects

• Machine Learning Specialization

• IBM Machine Learning Professional Certificate

• Structuring Machine Learning Projects

• Understanding Machine Learning 

Enroll today (teams & executives are welcome).  

Much career success, Lawrence E. Wilson - AI Academy (share with your team)