Learn ML With Python Offline

Developer: Incognito Inventions

Category: Education

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12.7K installs

27 ratings

52 monthly active users

$<10K monthly revenue est.

IAP 0% · Ad 100%

Install Trends

Weekly +5.00

Declining

Monthly +55

Steady

ASO Keyword Dashboard

Tracking 48 keywords for Learn ML With Python Offline in Google Play

Developer: Incognito Inventions Category: education

Learn ML With Python Offline tracks 48 keywords (1 keyword ranks; 47 need traction). Key metrics: 0% top-10 coverage, opportunity 70.1, difficulty 47.1, best rank 11.

Machine Learning With Python Quick Offline Guide

Tracked keywords

1 ranked • 47 not ranking yet

Top 10 coverage

Best rank 11 • Latest leader —

Avg opportunity

70.1

Top keyword: object

Avg difficulty

47.1

Lower scores indicate easier wins

Opportunity leaders

object

Opportunity: 74.0 • Difficulty: 42.3 • Rank —

Competitors: 679
62.8
nearest

Opportunity: 74.0 • Difficulty: 42.5 • Rank —

Competitors: 873
65.8
properly

Opportunity: 74.0 • Difficulty: 38.9 • Rank —

Competitors: 302
60.3
covering

Opportunity: 74.0 • Difficulty: 40.8 • Rank —

Competitors: 389
65.3
machine

Opportunity: 74.0 • Difficulty: 45.7 • Rank —

Competitors: 1,216
65.9

Unranked opportunities

object

Opportunity: 74.0 • Difficulty: 42.3 • Competitors: 679
nearest

Opportunity: 74.0 • Difficulty: 42.5 • Competitors: 873
properly

Opportunity: 74.0 • Difficulty: 38.9 • Competitors: 302
covering

Opportunity: 74.0 • Difficulty: 40.8 • Competitors: 389
machine

Opportunity: 74.0 • Difficulty: 45.7 • Competitors: 1,216

High competition keywords

easy

Total apps: 326,565 • Major competitors: 16,152

Latest rank: — • Difficulty: 56.4
free

Total apps: 323,639 • Major competitors: 24,336

Latest rank: — • Difficulty: 58.7
help

Total apps: 283,445 • Major competitors: 15,667

Latest rank: — • Difficulty: 58.5
using

Total apps: 221,131 • Major competitors: 12,080

Latest rank: — • Difficulty: 56.7
start

Total apps: 201,871 • Major competitors: 13,032

Latest rank: — • Difficulty: 56.1

All tracked keywords

Includes opportunity, difficulty, rankings and competitor benchmarks

							Major Competitors
machine learning	72	100	50	51 1,591 competing apps Median installs: 1,372 Avg rating: 3.9	15	11	65 major competitor apps
free	65	100	59	88 323,639 competing apps Median installs: 5,447 Avg rating: 4.1	—	—	24,336 major competitor apps
offline	68	100	54	80 112,788 competing apps Median installs: 4,209 Avg rating: 4.1	—	—	7,053 major competitor apps
easy	65	100	56	88 326,565 competing apps Median installs: 2,519 Avg rating: 4.0	—	—	16,152 major competitor apps
step	69	100	51	78 84,659 competing apps Median installs: 1,455 Avg rating: 4.0	—	—	4,173 major competitor apps
learn	67	100	55	82 144,381 competing apps Median installs: 2,286 Avg rating: 4.1	—	—	7,145 major competitor apps
content	67	100	56	82 131,764 competing apps Median installs: 2,364 Avg rating: 4.1	—	—	6,183 major competitor apps
using	66	100	57	85 221,131 competing apps Median installs: 2,891 Avg rating: 3.9	—	—	12,080 major competitor apps
basic	71	100	49	73 38,562 competing apps Median installs: 3,439 Avg rating: 4.0	—	—	1,889 major competitor apps
help	65	100	58	87 283,445 competing apps Median installs: 2,020 Avg rating: 4.1	—	—	15,667 major competitor apps
search	67	100	58	82 131,916 competing apps Median installs: 3,369 Avg rating: 4.1	—	—	6,891 major competitor apps
students	70	100	46	76 58,379 competing apps Median installs: 1,018 Avg rating: 4.0	—	—	728 major competitor apps
start	66	100	56	84 201,871 competing apps Median installs: 2,641 Avg rating: 4.0	—	—	13,032 major competitor apps
want	66	100	54	84 190,764 competing apps Median installs: 3,680 Avg rating: 4.0	—	—	11,477 major competitor apps
always	67	100	53	82 141,759 competing apps Median installs: 1,749 Avg rating: 4.1	—	—	6,547 major competitor apps
performance	69	100	48	77 66,545 competing apps Median installs: 943 Avg rating: 4.0	—	—	1,999 major competitor apps
feature	69	100	53	78 76,334 competing apps Median installs: 3,130 Avg rating: 4.0	—	—	4,585 major competitor apps
know	67	100	54	82 132,353 competing apps Median installs: 2,068 Avg rating: 4.1	—	—	6,034 major competitor apps
original	71	100	51	72 34,062 competing apps Median installs: 6,302 Avg rating: 4.1	—	—	2,774 major competitor apps
please	67	100	53	81 127,905 competing apps Median installs: 5,020 Avg rating: 4.1	—	—	6,917 major competitor apps
guide	69	100	48	77 72,103 competing apps Median installs: 1,452 Avg rating: 4.0	—	—	2,221 major competitor apps
quick	67	100	55	82 143,237 competing apps Median installs: 1,456 Avg rating: 4.0	—	—	6,861 major competitor apps
object	74	100	42	63 8,765 competing apps Median installs: 8,075 Avg rating: 4.0	—	—	679 major competitor apps
understand	70	100	48	76 57,150 competing apps Median installs: 1,801 Avg rating: 4.1	—	—	1,816 major competitor apps
data	66	100	57	84 182,626 competing apps Median installs: 1,338 Avg rating: 4.0	—	—	7,206 major competitor apps

App Description

Machine Learning With Python Quick Offline Guide

This FREE app will help you to understand ML With Python Tutorial properly and teach you about how to Start Coding using ML With Python. Here we are covering almost all Classes, Functions, Libraries, attributes, references. The sequential tutorial let you know from basic to advance level.

This "ML With Python Tutorial" is helpful for students to learn Coding step by step from basic to advance level.

***FEATURES***
* FREE of Cost
* Easy to Learn Programming
* ML With Python Basic
* ML With Python Advance
* ML With Python Object Oriented
* ML With Python Offline Tutorial

***LESSONS***
ML With Python Basic Tutorial

Python Ecosystem
Methods for Machine Learning
Data Loading for ML Projects
Understanding Data with Statistics
Understanding Data with Visualization

Preparing Data
Data Feature Selection
Introduction
Logistic Regression
Support Vector Machine(SVM)

Decision Tree
Naïve Bayes
Random Forest
Overview

Linear Regression
Overview
K-Means Algorithm
Mean Shift Algorithm
Hierarchical Clustering

Finding Nearest Neighbors
Performance Metrics
Automatic Workflows
Improving Performance of ML Models

Disclaimer :
All of content in this application is not our trademark. We only get the content from search engine and website. Please let me know if your original content want to remove from our application.

We are always here to help you.