# Meri Nova

Your guide to the latest ML and data-driven ventures. Learn from our guests who are senior engineers and entrepreneurs in Big Tech and Startups.

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## How to build a Machine Learning portfolio in 2024?

DevFeed: [How to build a Machine Learning portfolio in 2024?](<https://devfeed.tech/articles/how-to-build-a-machine-learning-portfolio-in-2024-39163.md>)

Original publisher: [Read original article](<https://merinova.substack.com/p/how-to-build-a-machine-learning-portfolio>)

Author: Meri Nova

Published: 2024-10-16T19:14:35Z

Content type: tutorial

Language: en

Sources: [Meri Nova](<https://devfeed.tech/sources/meri-nova.md>)

Topics: [Machine Learning & Artificial Intelligence](<https://devfeed.tech/topics/machine-learning-artificial-intelligence.md>), [AI Engineering](<https://devfeed.tech/topics/ai-engineering.md>), [Software Engineering](<https://devfeed.tech/topics/software-engineering.md>), [clean-code](<https://devfeed.tech/topics/clean-code.md>)

Tags: [ai-engineering](<https://devfeed.tech/tags/ai-engineering.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [ml-engineering](<https://devfeed.tech/tags/ml-engineering.md>), [practical](<https://devfeed.tech/tags/practical.md>), [project](<https://devfeed.tech/tags/project.md>), [real-world](<https://devfeed.tech/tags/real-world.md>)

### AI overview

A practical guide to building a machine learning portfolio around a focused area of expertise. It presents the STEP framework: solve real-world problems, use relevant tools, follow strong engineering practices, and publish documented impact.

### Source excerpt

Learn about the 4 essential components of an outstanding ML portfolio and land your dream job.

## How to break into data in 2024? With DataCamp's CEO, Jonathan Cornelissen.

DevFeed: [How to break into data in 2024? With DataCamp's CEO, Jonathan Cornelissen.](<https://devfeed.tech/articles/how-to-break-into-data-in-2024-with-datacamp-s-ceo-jonathan-cornelissen-39161.md>)

Original publisher: [Read original article](<https://merinova.substack.com/p/how-to-break-into-data-in-2024-with>)

Author: Meri Nova

Published: 2024-10-09T17:31:09Z

Content type: opinion

Language: en

Sources: [Meri Nova](<https://devfeed.tech/sources/meri-nova.md>)

Topics: [Data Science](<https://devfeed.tech/topics/data-science.md>), [data analytics](<https://devfeed.tech/topics/data-analytics.md>), [genai](<https://devfeed.tech/topics/genai.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [DataOps](<https://devfeed.tech/topics/dataops.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [beginners](<https://devfeed.tech/tags/beginners.md>), [career-advice](<https://devfeed.tech/tags/career-advice.md>), [data](<https://devfeed.tech/tags/data.md>), [data-analytics](<https://devfeed.tech/tags/data-analytics.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [education](<https://devfeed.tech/tags/education.md>), [future-of-work](<https://devfeed.tech/tags/future-of-work.md>), [genai](<https://devfeed.tech/tags/genai.md>), [podcast](<https://devfeed.tech/tags/podcast.md>), [scaling](<https://devfeed.tech/tags/scaling.md>), [technical](<https://devfeed.tech/tags/technical.md>)

### AI overview

A Technical Founder podcast episode featuring DataCamp co-founder and CEO Jonathan Cornelissen. The discussion covers building DataCamp, entering data careers, data education, GenAI's impact on edtech, data literacy, and career advice for new graduates.

### Source excerpt

Listen to our first episode of the "Technical Founder" podcast, where we invite AI and Data leaders to learn from their entrepreneurial and technical journey!

## Four LLM Engineering Tracks: Prompt Engineering, RAG, Fine-Tuning, and Model Pre-Training

DevFeed: [Four LLM Engineering Tracks: Prompt Engineering, RAG, Fine-Tuning, and Model Pre-Training](<https://devfeed.tech/articles/4-main-llm-engineering-levels-which-one-should-you-choose-39158.md>)

Original publisher: [Read original article](<https://merinova.substack.com/p/4-main-llm-engineering-levels-which>)

Author: Meri Nova

Published: 2024-09-12T21:47:45Z

Content type: article

Language: en

Sources: [Meri Nova](<https://devfeed.tech/sources/meri-nova.md>)

Topics: [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Prompt Engineering](<https://devfeed.tech/topics/prompt-engineering.md>), [Retrieval Augmented Generation (RAG)](<https://devfeed.tech/topics/retrieval-augmented-generation-rag.md>), [Development](<https://devfeed.tech/topics/development.md>), [Fine-tuning](<https://devfeed.tech/topics/fine-tuning.md>), [Machine Learning & Artificial Intelligence](<https://devfeed.tech/topics/machine-learning-artificial-intelligence.md>)

Tags: [engineering](<https://devfeed.tech/tags/engineering.md>), [fine-tuning](<https://devfeed.tech/tags/fine-tuning.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [llm](<https://devfeed.tech/tags/llm.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [ml](<https://devfeed.tech/tags/ml.md>), [prompt-engineering](<https://devfeed.tech/tags/prompt-engineering.md>), [rag](<https://devfeed.tech/tags/rag.md>)

### AI overview

The article presents four LLM engineering tracks and discusses their technical limitations, business opportunities, and implications for ML careers. It introduces a progression from prompt engineering and RAG to fine-tuning and pre-training models from scratch.

### Source excerpt

Learn about 4 unspoken levels of LLM engineering and how it impacts your ML career. Choose your roadmap from Prompt Engineering and RAG to pre-training models from scratch.

## Choosing the Right Machine Learning Algorithm for Business Problems

DevFeed: [Choosing the Right Machine Learning Algorithm for Business Problems](<https://devfeed.tech/articles/the-ultimate-guide-to-choosing-the-right-machine-learning-algorithm-from-day-one-39166.md>)

Original publisher: [Read original article](<https://merinova.substack.com/p/the-ultimate-guide-to-choosing-the>)

Author: Meri Nova

Published: 2024-05-24T19:01:02Z

Content type: tutorial

Language: en

Sources: [Meri Nova](<https://devfeed.tech/sources/meri-nova.md>)

Topics: [Machine Learning & Artificial Intelligence](<https://devfeed.tech/topics/machine-learning-artificial-intelligence.md>), [Algorithms](<https://devfeed.tech/topics/algorithms.md>), [Data Science](<https://devfeed.tech/topics/data-science.md>), [Framework](<https://devfeed.tech/topics/framework.md>)

Tags: [algorithm](<https://devfeed.tech/tags/algorithm.md>), [framework](<https://devfeed.tech/tags/framework.md>), [guide](<https://devfeed.tech/tags/guide.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>)

### AI overview

A step-by-step guide to choosing machine learning models for business problems using the CRISP-DM framework. It covers business requirements, data understanding and preparation, model selection, and evaluation.

### Source excerpt

Discover how to choose ML models for your business problems with this step-by-step guide using the CRISP-DM framework.

## Build and Deploy your first ML model with a 30-Day Challenge from Break Into Data Community.

DevFeed: [Build and Deploy your first ML model with a 30-Day Challenge from Break Into Data Community.](<https://devfeed.tech/articles/build-and-deploy-your-first-ml-model-with-a-30-day-challenge-from-break-into-data-community-39159.md>)

Original publisher: [Read original article](<https://merinova.substack.com/p/build-and-deploy-your-first-ml-model>)

Author: Meri Nova

Published: 2024-04-23T20:32:15Z

Content type: article

Language: en

Sources: [Meri Nova](<https://devfeed.tech/sources/meri-nova.md>)

Topics: [Hackathon](<https://devfeed.tech/topics/hackathon.md>), [Machine Learning & Artificial Intelligence](<https://devfeed.tech/topics/machine-learning-artificial-intelligence.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>)

Tags: [building](<https://devfeed.tech/tags/building.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [deploy](<https://devfeed.tech/tags/deploy.md>), [hackathon](<https://devfeed.tech/tags/hackathon.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>)

### AI overview

Break Into Data announces a free 30-day challenge starting May 1, 2024, where participants form teams to build and deploy machine learning models using large datasets, cloud services, and ML and data tools. The challenge emphasizes an end-to-end portfolio project and includes opportunities to present the best three projects.

### Source excerpt

Join us on a FREE 30-Day challenge that starts on May 1st, 2024. Learn about the structure of the challenge and find a registration form at the end.

## How We Implemented Large Language Models (LLMs) in the 'Break Into Data' Server in 3 Simple Steps

DevFeed: [How We Implemented Large Language Models (LLMs) in the 'Break Into Data' Server in 3 Simple Steps](<https://devfeed.tech/articles/how-we-implemented-large-language-models-llms-in-the-break-into-data-server-in-3-simple-steps-39165.md>)

Original publisher: [Read original article](<https://merinova.substack.com/p/how-we-implemented-large-language>)

Author: Meri Nova

Published: 2024-02-22T00:19:17Z

Content type: tutorial

Language: en

Sources: [Meri Nova](<https://devfeed.tech/sources/meri-nova.md>)

Topics: [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Discord](<https://devfeed.tech/topics/discord.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [OpenAI](<https://devfeed.tech/topics/openai.md>)

Tags: [database](<https://devfeed.tech/tags/database.md>), [discord](<https://devfeed.tech/tags/discord.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [integrate](<https://devfeed.tech/tags/integrate.md>), [large-language-models-llms](<https://devfeed.tech/tags/large-language-models-llms.md>), [llm](<https://devfeed.tech/tags/llm.md>), [messages](<https://devfeed.tech/tags/messages.md>), [openai](<https://devfeed.tech/tags/openai.md>)

### AI overview

A tutorial describing how the Break Into Data Discord community replaced screenshot-based accountability tracking with an LLM integration that parses natural-language submissions into structured metrics stored in a database. The article explains the limitations of the previous system and the tradeoffs between using forms and an LLM.

### Source excerpt

Learn How To Integrate OpenAI's LLM to Parse, Organize, and Store Discord Messages in A Database.

## How to contribute to Open Source for the first time?

DevFeed: [How to contribute to Open Source for the first time?](<https://devfeed.tech/articles/how-to-contribute-to-open-source-for-the-first-time-39164.md>)

Original publisher: [Read original article](<https://merinova.substack.com/p/how-to-contribute-to-open-source>)

Author: Meri Nova

Published: 2024-02-12T17:46:06Z

Content type: tutorial

Language: en

Sources: [Meri Nova](<https://devfeed.tech/sources/meri-nova.md>)

Topics: [Open Source](<https://devfeed.tech/topics/open-source.md>), [GitHub](<https://devfeed.tech/topics/github.md>), [Development](<https://devfeed.tech/topics/development.md>), [Pull Request](<https://devfeed.tech/topics/pull-request.md>), [Git](<https://devfeed.tech/topics/git.md>)

Tags: [contribute](<https://devfeed.tech/tags/contribute.md>), [fork](<https://devfeed.tech/tags/fork.md>), [git](<https://devfeed.tech/tags/git.md>), [github](<https://devfeed.tech/tags/github.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [programming](<https://devfeed.tech/tags/programming.md>), [pull-request](<https://devfeed.tech/tags/pull-request.md>)

### AI overview

A beginner-oriented tutorial explains why open-source contributions can provide practical collaborative experience and outlines a nine-step path to making a first contribution, including finding a project and issue, reviewing contribution guidelines, forking, and creating a branch.

### Source excerpt

It is easier than you think. Follow this 9-step guideline to make your first contribution on Github with the help of active community.