David TCHATCHOUA
MLOps/Data Scientist
Harvard Graduated in Machine Learning
ESLSCA Paris Business School
École d'Économie-CERDI-UCA
About Me
As a passionate, ambitious, and diligent MLOps professional, I possess extensive expertise in deploying machine learning applications across various cloud platforms, including AWS, Google Cloud Platform, and Azure Cloud, complemented by comprehensive tutorials for each. Below, you will find a table outlining my additional skills. I am also known for my meticulousness, analytical prowess, independence, and collaborative spirit. Furthermore, the tables below details my favorite hobbies, aspirations, and contact information.
| Area of Expertise | Skills & Technologies | Platforms & Tools |
|---|---|---|
| Cloud Platform Deployment | Deploying ML Applications | AWS Fargate, GCP, Azure Cloud |
| Model Building, Deployment & Monitoring | Building, Training, Deploying and Monitoring models | AWS SageMaker, Vertex AI, Azure ML, Hugging Face, OpenAI, Drift Detection |
| App Development & Deployment | Developing Gradio apps, Streamlit Apps | Docker, Kubernetes, Hugging Face, OpenAI, Render, OVH, Heroku |
| ML Pipelines | Exploring ML pipelines | MLFlow, MLRun, ZenML, Pycaret, DVC, KubeFlow, tfX |
| Advanced Technologies | ML, DL, Computer Vision, LLMs, Encoders, Transformers, GPU, CUDA | Pytorch, OpenAI API, LLama2, BERT, LangChain, RAG, Prompt Engineering |
| Specializations | Machine Learning, Deep Learning, Natural Processing Language, Generative AI, LLMOps, Computer Vision |
Hadoop, Spark, Ray, NoSQL, Tableau, Power Bi, Google Big Query, Tibco Spotfire, VS Code, Eclipse, Pycharm, Bash, Powershell, Git, Github Actions, Jenkins, Ansible, Terraform, Features sets, Features Vectors, Packages (Bandit, Safety, Poetry, Hyperopt, Optuna, Sha, Pytest, etc. ), Implementing MLOPS with RUST. |
MLOPS Professional Tutorials
| Number | Subjects | Links |
|---|---|---|
| 1 | How to Deploy ML flask App in AWS Fargate solution | Youtube | Github |
| 2 | How to Deploy ML flask App in Google Cloud Platform (GCP) | Youtube | Github |
| 3 | How to Deploy ML flask App in Azure Cloud | Youtube | Github |
| 4 | How to Build, Train and Deploy Models in AWS Sagemaker | Youtube | Github |
| 5 | How to Build Gradio app and Deploy in Hugging Face | Youtube | Github |
| 6 | How to Build Streamlit app and Deploy in Render | Youtube | Github |
| 7 | How to Build ML Pipelines with ZenML | Youtube | Github |
| 8 | How to Build ML Pipelines with Pycaret and MLflow | Youtube | Github |
| 9 | Computation of Predictions, Overall Accuracy, Variable Importance on iris dataset | Youtube | Github |
| 10 | Computation of RMSE (Root-Mean-Square Error) on a Linear Regression Model in R | Youtube | Github |
| 11 | Does Sample Size have an Impact on RMSE (Root Mean Square Error) ? | Youtube | Github |
| 12 | What Happens to RMSE when Dependent and Independent Variables are Highly Correlated ? | Youtube | Github |
| 13 | What Happens to RMSE when the Vector of the Independent Variable Increases ? | Youtube | Github |
| 14 | What Happens to RMSE when Independent Variables are Highly Correlated ? | Youtube | Github |
| 15 | Computer Vision : Objects Detection | Github |
| 16 | Build and Train a large Language Model (LLM) from scratch | Github |
| 17 | Test my Email Spam Classifier | Email Spam Classifier |
| 18 | Models Evaluation in Machine Learning | Youtube |
| 19 | Summary Statistics in Python | Youtube |
| 20 | Pandas Library | Youtube |
| 21 | Numpy Library | Youtube |
| 22 | Standard Deviation and Variance | Youtube |
| 23 | Introduction to Machine Learning | Youtube |
| 24 | Data Types in Python | Youtube |
CV
| Years | Position | Company et Location | Achievement |
|---|---|---|---|
| Current Position | MLOps and Data Scientist Trainer | Frenchtech- academie Pau, Paris, Geneva |
Development of MLOps, LLMOps and Data Scientist Tutorials and Courses. |
| 2021 - 2022 | Data Scientist | TotalEnergies Pau, France | Development of a data analysis workflow in R and Python, comparative analysis between Power Bi and Tibco Spotfire, working in Agile mode, use of API Rest, Jira and Machine learning models. |
| 2018 - 2019 | Structuring Assistant of Employee Savings and Retirement Funds | Amundi Asset Management Paris, France | VBA-Excel programming (macro creation for tracking funds performances), Access-VBA, SQL queries, fund management, data engineering, and data analysis. |
| 2018 | Financial Analyst | SA INVESTIR PUBLI- CATIONS - Les Echos Paris, France |
Writing of news/advice on listed stocks, daily on the website and for the weekly, analyzing and commenting on events that impact a stock. |
| 2017 | Research Assistant | INRA-AgroParisTech - LEF Nancy, France | Estimating the risk aversion and time preferences of forest owners. |
Courses
| Courses | Status |
|---|---|
| Machine Learning | Click here to Download |
| Deep Learning | Complete |
| Natural Language Processing | Complete |
| Data Science | Click here to Download |
| NoSQL Systems and Distributed Computing | Complete |
| Data Analysis | Complete |
| Azure Cloud | Complete |
| AWS | Complete |
| GCP | Complete |
| Docker | complete |
| Kubernetes | Complete |
| Jenkins | Complete |
| Python Data Structures | Click here to Download |
| Python for Data Science | Complete |
| R Studio | Click here to Download |
| Matlab | Complete |
| C/C++ | Complete |
| C# | Complete |
| PHP | Complete |
| Java | Complete |
| HTML | Complete |
| CSS | Complete |
| JavaScript | Complete |
| Excel-VBA | Complete |
| SQL | Complete |
| Wordpress | Complete |
| Wordpress WooCommerce | Complete |
| Python Django | Complete |
| PHP Symfony | Complete |
| Android | Complete |
| Scratch | Complete |
| Computer Systems and Networks | Complete |
| Programmation, Probabilities and Finance | Complete |
| Web development in PHP | Complete |
| Java Fullstack Developper | Complete |
| Power Bi | Click here to Download |
| Tibco Spotfire | Complete |
Technologies
| Programming Languages | Software | Tools |
|---|---|---|
| Python | TensorFlow | Jupyter Notebook |
| R | PyTorch | Git |
| Java | Keras | Docker |
| Scala | Scikit-learn | Kubernetes |
| Julia | MLflow | Apache Airflow |
| SQL | XGBoost | Ansible |
| JavaScript | LightGBM | Jenkins |
| Go | FastAI | Prometheus |
| C++ | H2O.ai | Grafana |
| Swift | Apache Spark | TensorBoard |
| Rust | Apache Airflow | Terraform |
| ...etc. | MLRun | AWS S3, ECR, ECS |
Publications, Papers, and Articles
| Type | Title | Year |
|---|---|---|
| Investment Bank Report | Implied Volatility Curves - Vanilla Options | 2018 |
| Finance Article | Une acquisition saluée par le marché | 2018 |
| Finance Article | Un chiffre d’affaires en hausse en tenant compte de la production en cours | 2018 |
| Finance Article | Alerte à la fraude ! | 2018 |
| Research Thesis | The Impact of Multinational Banks on African Household's Access to Credit | 2017 |
| Econometrics Article | Redistribution of Rents, Subsidies, and Fuel Prices in Sub-Saharan Africa | 2017 |
| Master 2 Internship Report | Estimating the Preferences of Forest Owners and Managers based on an Experiment | 2017 |
| Master 1 Internship Report | Approaches and Measures of Poverty: The Case of Morocco | 2016 |
| Research Thesis | The Impact of Regulation on the Small and Medium-sized Enterprises (SMEs) in Developing Countries | 2016 |
Favorite Interests
| Hobbies | Skills | Aspirations |
|---|---|---|
| Reading Editorials | Programming in Python | Learning a new Language |
| Hiking | Financial Markets | Becoming a Mentor |
| Golf | Macroeconomics | Traveling to every continent |
| Gourmet Cooking | Creative Writing | Launching an Entrepreneurial Project |
| Chess Playing | Project Management | Contributing to an Open-Source Project |
Contacts
| Contact Method | Details | Availability Hours |
|---|---|---|
| davidtchouta@gmail.com | Monday-Friday, 8am-5pm | |
| Phone |
+33 7 82 99 45 61 +41 78 310 57 62 |
Monday-Friday, 8am-6pm |
| David TCHATCHOUA | Available for messages | |
| Available for messages | ||
| Website | Académie Française du Numérique | Information available 24/7 |
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