#300 End to End AI Application Development with Maxime Labonne & Paul-Emil Iusztin
Skills:
Fine-tuning LLMs80%AI Systems Design80%Prompt Craft70%Tool Use & Function Calling70%AI Startup Building60%
The roles within AI engineering are as diverse as the challenges they tackle. From integrating models into larger systems to ensuring data quality, the day-to-day work of AI professionals is anything but routine. How do you navigate the complexities of deploying AI applications? What are the key steps from prototype to production? For those looking to refine their processes, understanding the full lifecycle of AI development is essential. Let's delve into the intricacies of AI engineering and the strategies that lead to successful implementation.
Maxime Labonne is a Senior Staff Machine Learning Scientist at Liquid AI, serving as the head of post-training. He holds a Ph.D. in Machine Learning from the Polytechnic Institute of Paris and is recognized as a Google Developer Expert in AI/ML. An active blogger, he has made significant contributions to the open-source community, including the LLM Course on GitHub, tools such as LLM AutoEval, and several state-of-the-art models like NeuralBeagle and Phixtral. He is the author of the best-selling book “Hands-On Graph Neural Networks Using Python,” published by Packt.
Paul-Emil Iusztin designs and implements modular, scalable, and production-ready ML systems for startups worldwide. He has extensive experience putting AI and generative AI into production. Previously, Paul was a Senior Machine Learning Engineer at Metaphysic.ai and a Machine Learning Lead at Core.ai. He is a co-author of The LLM Engineer's Handbook, a best seller in the GenAI space.
In the episode, Richie, Maxime, and Paul explore misconceptions in AI application development, the intricacies of fine-tuning versus few-shot prompting, the limitations of current frameworks, the roles of AI engineers, the importance of planning and evaluation, the challenges of deployment, and the future of AI integration, and much more.
Find DataFramed on DataCamp https://www.datacamp.com/podcast
and on your preferred podcast streaming platform:
Apple Podcasts:
https://podc
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
Playlist
Uploads from DataCamp · DataCamp · 0 of 60
← Previous
Next →
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
SQL Server Tutorial: Date manipulation
DataCamp
R Tutorial: Intermediate Interactive Data Visualization with plotly in R
DataCamp
R Tutorial: Adding aesthetics to represent a variable
DataCamp
R Tutorial: Moving Beyond Simple Interactivity
DataCamp
Python Tutorial: Why use ML for marketing? Strategies and use cases
DataCamp
Python Tutorial: Preparation for modeling
DataCamp
Python Tutorial: Machine Learning modeling steps
DataCamp
R Tutorial: The prior model
DataCamp
R Tutorial: Data & the likelihood
DataCamp
R Tutorial: The posterior model
DataCamp
R Tutorial: An Introduction to plotly
DataCamp
R Tutorial: Plotting a single variable
DataCamp
R Tutorial: Bivariate graphics
DataCamp
Python Tutorial: Customer Segmentation in Python
DataCamp
Python Tutorial: Time cohorts
DataCamp
Python Tutorial: Calculate cohort metrics
DataCamp
Python Tutorial: Cohort analysis visualization
DataCamp
R Tutorial: Building Dashboards with flexdashboard
DataCamp
R Tutorial: Anatomy of a flexdashboard
DataCamp
R Tutorial: Layout basics
DataCamp
R Tutorial: Advanced layouts
DataCamp
Python Tutorial: Time Series Analysis in Python
DataCamp
Python Tutorial: Correlation of Two Time Series
DataCamp
Python Tutorial: Simple Linear Regressions
DataCamp
Python Tutorial: Autocorrelation
DataCamp
R Tutorial: The gapminder dataset
DataCamp
R Tutorial: The filter verb
DataCamp
R Tutorial: The arrange verb
DataCamp
R Tutorial: The mutate verb
DataCamp
R Tutorial: What is cluster analysis?
DataCamp
R Tutorial: Distance between two observations
DataCamp
R Tutorial: The importance of scale
DataCamp
R Tutorial: Measuring distance for categorical data
DataCamp
Python Tutorial: Plotting multiple graphs
DataCamp
Python Tutorial: Customizing axes
DataCamp
Python Tutorial: Legends, annotations, & styles
DataCamp
Python Tutorial: Introduction to iterators
DataCamp
Python Tutorial: Playing with iterators
DataCamp
Python Tutorial: Using iterators to load large files into memory
DataCamp
SQL Tutorial: Introduction to Relational Databases in SQL
DataCamp
SQL Tutorial: Tables: At the core of every database
DataCamp
SQL Tutorial: Update your database as the structure changes
DataCamp
Python Tutorial: Classification-Tree Learning
DataCamp
Python Tutorial: Decision-Tree for Classification
DataCamp
Python Tutorial: Decision-Tree for Regression
DataCamp
Python Tutorial: Census Subject Tables
DataCamp
Python Tutorial: Census Geography
DataCamp
Python Tutorial: Using the Census API
DataCamp
R Tutorial: A/B Testing in R
DataCamp
R Tutorial: Baseline Conversion Rates
DataCamp
R Tutorial: Designing an Experiment - Power Analysis
DataCamp
R Tutorial: Introduction to qualitative data
DataCamp
R Tutorial: Understanding your qualitative variables
DataCamp
R Tutorial: Making Better Plots
DataCamp
SQL Tutorial: OLTP and OLAP
DataCamp
SQL Tutorial: Storing data
DataCamp
SQL Tutorial: Database design
DataCamp
Python Tutorial: Introduction to spaCy
DataCamp
Python Tutorial: Statistical Models
DataCamp
Python Tutorial: Rule-based Matching
DataCamp
More on: Fine-tuning LLMs
View skill →
Related AI Lessons
⚡
⚡
⚡
⚡
DE LA GENÈSE À L’INSTITUTION: L’ANATOMIE DU PASSAGE DE STARTUP À ENTREPRISE
Medium · Startup
The Kenyan Boeing engineer who chose trucks over prestige
TechCabal
Why More Startups Are Hiring Interim Finance Directors Instead of Full-Time CFOs
Medium · Startup
Universal High Income: Will a Labor-Free Future Bring True Happiness?
Medium · AI
🎓
Tutor Explanation
DeepCamp AI