Data Science & Machine Learning-training-in-bangalore-by-zekelabs

Data Science & Machine Learning Training

Data Science & Machine Learning 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-training-in-bangalore-by-zekelabs
Data Science & Machine Learning-training-in-bangalore-by-zekelabs
Industry Level Projects
Data Science & Machine Learning-training-in-bangalore-by-zekelabs

Data Science & Machine Learning Course Curriculum

What is not Machine Learning
Types of ML - Supervised, Unsupervised
Unsupervised - Clustering, Association
Introduction to NumPy
Introduction to Pandas
Loading CSV,JSON
Descriptive Statistics
Handling Missing Data
Handling Duplicates
Merge, Join & Concatenate
Normalizing JSON
Essential Linear Algebra
Mean, Median, Mode, Quantile
Introduction to matplotlib, plotly, bokeh, tablue
Title, Labels, Legends, Grid, colormap, xticks, yticks
Sub Plotting
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
Encoding Categorical (Ordinal & Nominal) Features
Polynomial Features
Text Processing
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
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
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 ?
Making classification algorithm aware of Imbalance
Application - Fraud detection
Introduction to Ensemble Methods
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

We have options for classroom-based as well as instructor led live online training. The online training is live and the instructors screen will be visible and voice will be audible. Your screen will also be visible and you can ask queries during the live session.

The training on "Data Science & Machine Learning Foundation" course is a hands-on training. All the code and exercises will be done in the live sessions. Our batch sizes are generally small so that personalized attention can be given to each and every learner.

We will provide course-specific study material as the course progresses. You will have lifetime access to all the code and basic settings needed for this "Data Science & Machine Learning Foundation" through our GitHub account and the study material that we share with you. You can use that for quick reference

Feel free to drop a mail to us at [email protected] and we will get back to you at the earliest for your queries on "Data Science & Machine Learning Foundation" course.

We have tie-ups with a number of hiring partners and and placement assistance companies to whom we connect our learners. Each "Data Science & Machine Learning Foundation" course ends with career consulting and guidance on interview preparation.

Minimum 2-3 projects of industry standards on "Data Science & Machine Learning Foundation" will be provided.

Yes, we provide course completion certificate to all students. Each "Data Science & Machine Learning Foundation" training ends with training and project completion certificate.

You can pay by card (debit/credit), cash, cheque and net-banking. You can also pay in easy installments. You can reach out to us for more information.

We take pride in providing post-training career consulting for "Data Science & Machine Learning Foundation".

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