Python and Machine Learning
Languages
English
Batch Size
40-50
Duration
45 hours
Course Contents
- Data Science, Machine Learning and its applications
- Data Visualization
- Supervised and unsupervised algorithms
- Analytics solutions and assessment of their effectiveness
- Introduction
- Data Science
- Data Scientist
- Artificial Intelligence vs Machine Learning vs Deep Learning
- Statistical vs Machine Learning Approaches
- Big Data
- Data Life Cycle
- OSEMN - Obtain, Scrub, Explore, Model, and iNterpret
- Data
- Data sources
- Obtaining the data
- Data preparation
- Identification of data requirements
- Data quality
- Duplicate, missing, and incomplete data
- Exploratory Data Analysis
- Introduction
- Data Visualization
- Data Mining
- Data Wrangling
- Data Cleaning
- Data Preparation (for the model)
- Feature Engineering - Feature Scaling and Standardization
- Univariate Analysis + Multivariate Analysis + Correlation
- Descriptive statistics
- Inferences from Visualization
- Seaborn
- Matplotlib
- Supervised Learning
- Supervised Learning Algorithms
- Regression
- Classification
- Logistic
- Decision Tree, Training and Visualization
- Classification And Regression Trees (CART)
- Random Forest
- Support Vector Machine
- K-Nearest Neighbour
- Case study
- Model Improvement
- Association and dependence
- Differences between causation and correlation
- Simpson’s paradox
- Curse of Dimensionality (COD)
- Bias-variance trade-off
- Train-test split
- K-fold cross-validation
- Evaluation of models
- Comparison of model performance
- Computational Complexity
- Gini Impurity or Entropy
- Regularization Hyperparameters
- Unsupervised Learning
- Different Clustering techniques
- K-Means Clustering
- K-Means Algorithm
- Benefits of using K-Means Clustering
- Problems & Use Cases
- Industry Readiness - Project
Basic Python programming knowledge
Software options: Anaconda Navigator: https://www.anaconda.com/products/individual OR Google Colab: https://colab.research.google.com/
Instructor Profile
Dr. Roy is an expert in the field of Statistics, Data Science, Quality and Cyber Security with 20+ years of experience of training and teaching professionals & students in these areas. Many of his students are working in reputed companies.
This course includes:
100% Online Sessions
Instructor led
Customizable Syllabus
Customizable Schedule
Certificate of Completion
Training Recordings
Training Resources
Learner Assessment
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