Data Science & Machine Learning Foundation Training
Data Science & Machine Learning Foundation Course:
Machine Learning is one the hottest technology trending these days. This course covers every aspect of machine learning from thinking, development & deployment. More than 10 projects of different domains are covered. It uses scikit-learn for machine learning & pandas for data wrangling. It's a very hands-on course. Code is public & have around 500 stars. The use cases are from different companies.
Data Science & Machine Learning Foundation Course Curriculum
What is not Machine Learning
Types of ML - Supervised, Unsupervised
Unsupervised - Clustering, Association
Introduction to NumPy
Access
Methods
Introduction to Pandas
Loading CSV,JSON
Descriptive Statistics
Handling Missing Data
Handling Duplicates
Merge, Join & Concatenate
Normalizing JSON
Essential Linear Algebra
Calculus
Mean, Median, Mode, Quantile
Introduction to matplotlib, plotly, bokeh, tablue
Title, Labels, Legends, Grid, colormap, xticks, yticks
Sub Plotting
Histogram
Plotting distributions
Simple Linear Regression using Ordinary Least Squares
Regularized Regression Methods - Ridge, Lasso, ElasticNet
OnLine Learning Methods - Stochastic Gradient Descent & Passive Aggrasive
Polynomial Regression
Application - House Price, Cancer Prediction, Insurance Prediction
Introduction to Preprocessing
MinMaxScaler
Normalization
Encoding Categorical (Ordinal & Nominal) Features
Polynomial Features
Text Processing
TfIdf
Image using skimage
Introduction to Decision Trees
Decision Tree for Classification
Advantages & Limitations of Decision Trees
Introduction Bayes' Theorm
Gaussian Naive Bayes
Burnolis' Naive Bayes
Application - Text Classification
Introduction to Composite Estimators
TransformedTargetRegressor
ColumnTransformer
Application - Author classification
Cross Validation
Model Evaluation
Validation Curves
Introduction to Feature Selection
Chi-squared stats
Univariate Linear Regression Tests using f_regression
Mutual Information for discrete value
SelectKBest
SelectFromModel
PCA
Application - Credit Risk Prediction
Fundamentals of Nearest Neighbor Algorithm
Nearest Neighbors for Classification
Nearest Centroid Classifier
Introduction to Unsupervised Learning
Similarity or Distance Calculation
Types of Clustering Methods
Hierarchial Clustering - Agglomerative
Measuring Performance of Clusters
Application - Grouping similar customers
What are Outliers ?
Using Gaussian Mixture Models
Isolation Forest
Using clustering method like DBSCAN
Introduction to Support Vector Machines
Soft Margin Classifier
SVM for Regression
Application - Face recognition
What are imbalanced classes & their impact ?
UnderSampling
Making classification algorithm aware of Imbalance
Application - Fraud detection
Introduction to Ensemble Methods
AdaBoost
VotingClassifier
Understanding distance vector calculation - cosine, euclidean, manhatten
Recommendation based on similarity
Credit Risk Prediction
Face Generation
Network Spam detection
Cloth Type Prediction
Customer Churn Prediction
Frequently Asked Questions
This "Data Science & Machine Learning Foundation" course is an instructor-led training (ILT). The trainer travels to your office location and delivers the training within your office premises. If you need training space for the training we can provide a fully-equipped lab with all the required facilities. The online instructor-led training is also available if required. Online training is live and the instructor's screen will be visible and voice will be audible. Participants screen will also be visible and participants can ask queries during the live session.
Participants will be provided "Data Science & Machine Learning Foundation"-specific study material. Participants will have lifetime access to all the code and resources needed for this "Data Science & Machine Learning Foundation". Our public GitHub repository and the study material will also be shared with the participants.
All the courses from zekeLabs are hands-on courses. The code/document used in the class will be provided to the participants. Cloud-lab and Virtual Machines are provided to every participant during the "Data Science & Machine Learning Foundation" training.
The "Data Science & Machine Learning Foundation" training varies several factors. Including the prior knowledge of the team on the subject, the objective of the team learning from the program, customization in the course is needed among others. Contact us to know more about "Data Science & Machine Learning Foundation" course duration.
The "Data Science & Machine Learning Foundation" training is organised at the client's premises. We have delivered and continue to deliver "Data Science & Machine Learning Foundation" training in India, USA, Singapore, Hong Kong, and Indonesia. We also have state-of-art training facilities based on client requirement.
Our Subject matter experts (SMEs) have more than ten years of industry experience. This ensures that the learning program is a 360-degree holistic knowledge and learning experience. The course program has been designed in close collaboration with the experts working in esteemed organizations such as Google, Microsoft, Amazon, and similar others.
Yes, absolutely. For every training, we conduct a technical call with our Subject Matter Expert (SME) and the technical lead of the team that undergoes training. The course is tailored based on the current expertise of the participants, objectives of the team undergoing the training program and short term and long term objectives of the organisation.
Drop a mail to us at [email protected] or call us at +91 8041690175 and we will get back to you at the earliest for your queries on "Data Science & Machine Learning Foundation" course.
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