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Linear Regression, Gradient Descent, Multicollinearity, VIF, R-square, Heteroscedasticity, Sklearn, Polynomial Regression, Bias-Variance trade-off, Regularisation.Functions, Limits, Derivatives, Partial derivatives, Saddle points.Line, Plane, HyperPlane, Half space, Classification using plane.Vector and Matrices, Dot product, Projections, System of Equations, Matrix Transformation, Eigen Vectors and Values, Orthonormal Basis Vectors, SVD, PCA.Risk, Product, Banking, Finance, E-Commerce, Social Media, Marketing, Transporation, Healthcare, Operations.Resampling, Autocorrelation, Forecasting, Seasonal Naive, Double/Triple Exponential (Holt) Residual Analysis, Stationarity tests, Autoregressive methods, moving average, ARIMA, SARIMA.Text and Image vectorization using Deep-Learning, Interpretable ML, ML Life Cycle.Dimentionality Reduction & Visualization, Anomaly Detection, K-Means, PCA, t-SNE.KNN, Linear Regression, Logistic Regression, Decision Trees, Feature importance, ML Metrics.ata Model: Data & Relationship View, Connecting Different Data sources, Data Modelling, Timeseries, Aggregation, and Filters, Maps, Plotting Techniques, Tables and Relation ships, Creating an Interactive Business Intelligence Report.

Creating objects, Matrices, Loops, Functions in R, Data Manipulation in R, Creating frequency tables and cross tables, Building charts, Performing univariate analysis, Working with dates and time in R, Dplyr, GGplot.

Getting Acclimated with EXCEL, Basic EXCEL Formulas & Functions, Text, Times, and Dates Data Formats, Pivot Table, Introduction to Statistics in EXCEL, Handling Data in EXCEL, Pivot Tables, Charts in Excel.Nested Queries, String Functions & Pattern Matching, Mathematical Functions, Date-Time Functions.Mapping Geographic Data, Using stories to build dashboards, Working with Times and Dates, Creating Conditional Calculations Using Logical Functions, Creating Level of Detail (LOD) Expressions, Summarizing Data Using Table Calculations, Managing Text Strings.Domain Knowledge - Banking, Finance, Marketing, Social Media, Operations, Healthcare.

#Stellar data recovery bangalore address how to#

How to crack Product and Strategy Rounds.

Creating Basic Charts, Dashboards & Actions.

Managing Data Sources and Visualizations.

EDA, Covariance, Correlation, Pearson, Spearman Rank, Multi-dimensional, Feature Engineering, Column normalisation, Standardisation, Covariance matrix, Missing Values, Outlier treatment.

Experiment Design, ANOVA, Simulations, Power of Test, A/B testing, Diff n Diff, Multi-arm bandits.

Hypothesis Testing, Parametric vs non-parametric, Z-test, Chi-square, Skewness, Kurtosis, Normality test.

Unstructured Data - OpenCV, Image processing, Smoothening, Morphological Operations, NLTK, Text processing.

Data from Web API, Scraping, Data Cleaning.

Relational, Non-relational, ER diagrams, SQL Commands, Aggregate Functions, Joins, SubQueries, Normalisation, Scaling patterns, ACID, Dask SQL, Cloud SQL (Athena/BigQuery).

Vector and Matrices, Unit Vector, Dot product, Projections, Cosine Similarity, Determinant, Transpose, System of Equations.

DF, PMF, CDF, PPF, Uniform, Gaussian, Bernoulli, Multinomial, Normal Distribution, Poisson, Exponential, Geometric, Log-normal distribution, Pareto/Power Law Distribution.

Combinatorics, Marginal Probability, Joint Probability, Conditional Probability, Bayes Theorem, Mean, Median, Mode, Percentile, IQR, Outlier.

Probability Theory and Desciptive Statistics.

Data Visualisation using Matplotlib and Seaborn.