Welcome!. My name is José Higuera and I'm a Data Scientits and Machine Learning engineer.
Courses that I have taken
Descriptive Statistic
- Qualitative, quantitative and ordinal data types and the correct analysis of each of them.
- Statistic values. Mean, Mode, Median, Kurtosis and Skew.
- Complete descriptive analysis.
- Using graphs to represent statistical data.
By:
Juan Gabriel Gomila Salas
Mathematician, specialized in data analysis for video game companies with R and Python.
Probability for Machine Learning
- Solve probability problems using R and Python.
- Concepts of correlation and independence of variables.
- Probability functions for discrete and continuous variables.
- Central Limit Theorem.
By:
Juan Gabriel Gomila Salas
Mathematician, specialized in data analysis for video game companies with R and Python.
Inferencial Statistic
- Solve problems about inferencia statistic.
- Estimate parameters of a population from a sample.
- Calculate and interpret a parametric and non-parametric hypothesis test.
- Fit using simple and multiple linear regression models.
By:
Juan Gabriel Gomila Salas
Mathematician, specialized in data analysis for video game companies with R and Python.
Data Science with Python
- Operations with data. Cleaning and preparation.
- Supervised and unsupervised learning.
- Build diverse Machine Learning models to solve problems. Understanding the results and making conclusions.
- Introduction to Neural Networks.
By:
Juan Gabriel Gomila Salas
Mathematician, specialized in data analysis for video game companies with R and Python.
Data Science School at Platzi
- Data visualization using Pandas, Matplotlib, seaborn.
- BI tools. Tableau, Power BI and Google Data Studio.
- Data Engineer tools, ETL, Web Scraping.
- Machine Learning models and Neural Networks.
By:
Platzy
Effective online professional education. Teachers are professionals who are currently applying the techniques they teach.
Artificial Intelligence
- Understand the concepts of modern artificial intelligence as well as Deep Learning and Q-Learning.
- Understand the most advanced aspects of artificial intelligence.
- ANN, CNN, RNN and others.
- The theory behind Deep Q Learning.
- Build neural networks.
By:
Juan Gabriel Gomila Salas
Mathematician, specialized in data analysis for video game companies with R and Python.
Machine Learning by Stanford
- Introduction to machine learning, datamining, and statistical pattern recognition.
- Supervised and Unsupervised learning.
- Linear regression, logistic regression, SVM, Neural Networks.
- Best practice in Machine Learning.
- Clustering, dimensionality reduction, recommender systems.
- Numerous case studies and applications. Such as anomalies detection, text understanding, anti-spam and others.
By:
Andrew NG
IA Research, Founder of DeepLearning.AI, Co-founder of Courcera
Deep Learning Specialization
- Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications.
- Build a CNN and apply it to detection and recognition tasks.
- Train test sets, analyze variance for DL applications.
- Build and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering
By:
Andrew NG
IA Research, Founder of DeepLearning.AI, Co-founder of Courcera
Tensorflow Mastery Cource
- Learn to build all types of Machine Learning Models using the latest TensorFlow 2
- Build image recognition, object detection, text recognition algorithms with deep neural networks and convolutional neural networks
- Applying Deep Learning for Time Series Forecasting
- Build TensorFlow models using Computer Vision, Convolutional Neural Networks and Natural Language Processing
By:
Daniel Bourke
Self-taught Machine Learning Engineer, ML Engineer on Australia Artificial intelligence Agency Max Kelsen
My Hobbies
Always Learning
I am on the side that we have to be updated all the time. In the Tech industry, the tools to create the magic are always in improvement, ve have to be as same time.
Photography
Photography helps me forget the routine, gives peace, tranquility, helps me meditate and order my emotional life.
Weather
Seeing those dark skies, seeing those gray clouds about to fall, is one of the best landscapes my eyes can see. Rainy days are the best.
Web Development
If I did not love data science, my first choice would be web development. So much so that I consider it as a second profession. It is analytical, it is creative and what we can create is out of the imagination.
Hard Skills
Programming Languages
Python/Notebooks
R & R-Studio
JavaScript
SQL
Data Operation
Cleaning
Operations
Transformation
Visualization
Maths
Statistics
Probability
Lineal Algebra
Calculus
ML Algorithms
Regressions
Clasifications
Clusters
Dim. Reduction
DL Algorithms
Regression NN
Classification NN
CNN
RNN
ML & DL Frameworks
Numpy
Pandas
Matplotlib
Scikit Learn
Tensorflow
BI Skills
Tableau
Power BI
Excel
Other Skills
Git-GitHub
Soft Skills
Teamwork
Communication
Leadership
Commitment
Curiosity
Responsibility